Honours Review 19

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“ ‘Getting lost’ is the occurrence of an individual losing their spatial reference, consisting of two elements: the feeling of disorientation and a spatial environment. The notion of getting lost constitutes part of the human experience of dayto-day life” (Solnit, 2014).

The Editorial Board Lost in Translation There is a particular kind of loneliness that comes not from being alone, but from being almost understood. As an international student, you learn to exist in the gaps — between languages, between versions of yourself, between the person you were at home and the one you’re still becoming here. There is a certain dance many of us perform, whether with each other or with those native to the country we now call home. Where are you from?

But where did you grow up? But where are your parents from? But why come here?

You carry a whole interior world that doesn’t quite fit into the conversations around you. Fluent enough to get by, but never fluent enough to feel real.

This creeping sense of uncertainty, disconnection, and alienation reshapes how we understand ourselves: our consciousness, our perception of the spaces we move through, and the version of ourselves we present to the world. You begin to wonder which self is the true one—the one who makes sense back home, or the one slowly, awkwardly taking shape here. Maybe both. Maybe neither, yet.

But there is beauty in this transition, too. It lives in the community you find in others who understand, not only fellow international students, but every young person navigating the disorienting work of becoming an adult.

Our authors in this issue have captured that silver lining with remarkable honesty: from personal reflections to scientific analyses, a shared thread runs through every piece. That translation, whether linguistic, cultural, or scientific, is never neutral.

We extend our deepest gratitude to our authors, Peer Review Panel, and our artists for their extraordinary contributions. We hope this issue offers you the same sense of fulfillment we found in piecing it together.

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Translation as Philosophical Constraint: From Event to Concept t , once or sometimes . e m s t i s i a scent v ery time.

I stop ev isle. a grocery ate. g t r airpo . important e r e h w e m so . e t I’m la damn it,

From Sarcasm

knocking,

t Translation destabilized the Hebrew Bible’s nt withou the prese form of revelation. When revelation tisslips through n. i mall agai rendered into another language — especially suddenly I am s nd a one governed by different epistemic , mom’s car assumptions and philosophical frameworks — t of your a ws, e o s d k n c i a w b , st the in the ambiguity becomes a problem to be resolved ing ahead urring pa z l z b u b m a t d n r e e m a n r Amst u . o rather than a space to be inhabited. Similar e t m to na Pokémon oo young our first to contemporary machine learning systems, we were t e s i m o r p which are designed to produce stable and out like a ives with repeatable outputs, translation exerts algia arr Tran sl scalea sofLegal Method t s ayation o r n g l e a h s t that na hrough t pressure toward resolution and coherence: e u l b Lawrence Venuti makes a useful distinction.6 Some translation domesticates, pulling f g and when rin n, flicke texts toward local norms and sanding off the strangeness. Other translation foreignizes, k multiple meanings are narrowed, de me i s e b permissio n w o markers of otherness intact. Venuti ties domestication to imperialism, arguing that s context-specific expressions are day, and sits d translation wipes away the source culture’s distinctiveness. Apply this to law, and you’ve got to left, r generalized, and narrative tensions are for seeing how recipient societies handle imported concepts. Do they absorb them into e e v e n t like i preserve their alien feel?

The Septuagint is frameworks? the Or ancient Greek stabilized. In religious contexts, this ay. t , s e m t i i t t e e h l t I l l a u translation of the Hebrew Bible (the Tanakh), pressure is inseparable from authority, since o y If you combine Venuti’s framework with Teubner’s irritant concept, a pattern reveals t u o b a nk rules2nd land incenturies a new system and cause disruption. The system respon ents. between the Transplanted 3rd and whoever resolves ambiguity determines whatI thi g momproduced n i s s a domesticating them, absorbing foreign content into local frameworks. What comes out the p e BCE, most likely in Alexandria. emerged in divine authority means and Anonymous how it may bein th French Business Administrator School, 2004 [1] lyis,a hybrid: tracesItof both end origin and destination, while on the whole being neither. M L

By Laura ,transforms in transit. o slowhad s o d t n a e l l t t t a point.

The original meaning But Watson had a point too i i l a multilingual environment where Greek was interpreted. (9) e r a u s s d e a k o a l m n o e t borrowing happens, and it produces working legal orders; The trick is recognizing tha e r e e c h c s t d the alongside Egyptian and , analong ame twi language, when a rereshaped a ndominant travels the way. The Japanese and Baltic cases show this playing out hegets w f no one saysPersian cultural The translation different timestand places, and they reveal how recipient cultures can strategically use tran by out oinfluences. s . t f when some s i a r p d e g h reshape what’s tto been imposed on them. ard Jewish eme son was undertaken communities whose ly towfor when a th o slightlanguage ver sprimary e s had become Greek,Domestication and it t l i t in Occ upied Ja room represents one of theInoue’searliest and most linguistic deep-dive reveals something remarkable. Japan’s constitution is rea influential instances large-scale documentsof wearing one title. The American version reflects Anglo-American political th The Japaneseshaping version? The language barrier, Inoue argues, remained intact throughout. A religious translation, later biggest gap opened around a single word: “the people.”

Christian and Jewish traditions.

to Ille

English is not the language of English speakers.

Historical Context: The Septuagint

It belongs to me too if I want to AI Mistran keep up my relations with the wider Speech, and world.“ in the Searc

R

s

While training an ML model for my purpose will (hopefully) allow me to achieve the abovementioned purpose, it is at the cost of information lost in other ways.

Machines evaluate answers based on input parameters, obtained from us. The evaluation process undergone by the machines is often very complex and non-linear, and therefore not transparent for interpretation by humans. Not understanding how a machine came to the answer they gave us inevitably causes a loss of information along the way.

In the case of distinguishing neutrons and photons, we have the data, but it is too complicated for simple models to classify, with thousands of interactions in a detector leading a single pulse. At high detected energies, the pulse shapes are very different, and a PSA suffices, however at low energies these blend together, and background photons become more significantly, leading to a PSA being unable to distinguish them. Following Acquaviva’s approach we can determine that ML is a fitting tool for tackling this task of translating data into scientific knowledge.

Speaking

However, it is because of this complexity that ML allows us to collect all kinds of invisible (to us) underlying correlations in the data, and predict based on that. However it is important to note that while this can seem to be ML exhibiting some kind of intellectual properties and ‘understanding’ the data, it is nothing other than reproducing past trends, without any critical evaluation of the input.

Borrowed Words, Contested Meanings

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⼈⺠

The American drafters chose jinmin ( ), a term with revolutionary undertones sugg citizens who hold ultimate political power. Japanese translators systematically replaced

The Septuagint was produced in), which a Hellenistic kokumin ( 国⺠ has a meaning closer to “national subjects” bound to the state Dower noticed this did: it shifted the constitutional foundation away from popular intellectual environment in whatwhich Greek and back toward the state and emperor. This was done quietly. Deliberately. Domestica philosophy shaped prevailing conceptions of action, reshaping American intent from within. logic, reason, and order. Greek was therefore not a neutral medium for Hebrew thought, but Hahm and Kim explored how “We the People” gets built through a language structured by the expectation that translation across East Asian constitutions. Whether you understand truth be coherent, stable, and conceptually the collective sovereign as autonomous citizens or as members tied to Tran sl ation a s Legal Resi stance in Occ upied Japan a nationalWithin whole has this real institutional consequences. The expressible. (10) framework, jinmin/kokumin swap was more than a word choice. It redefined, What do we makeand of these Power structures Post-S oviet ?Europe translation didsilently, notwhosimply holds power. transmit meaning

By M arta Liduma but reorganized it, introducing pressure to A similar process happened with “rights.” The word that stuck, kenri resolve ambiguity thecharacters levelmeaning of grammar and It lacks Introduc tion ( 権利 ),at combines “power” and “benefit.”

February 1946. A handful of Americans, most with limited knowledge of Japan, spend a single week drafting a the produced moral weight ofa natural rights talk. Hasegawa vocabulary.

This shift from actiondug into constitution in English for a defeated nation. Fast forward to 1991. Three Baltic states, freshly independent, start nineteenth-century debates and found that alternative translations to essence.preserving Dynamic, event-based weaving European human rights provisions into legal systems still shaped by Soviet thinking. What do these ethical meaning failed to gain traction. The result? on moments have in common? Both needed Western legal ideas to be rendered into languages and cultures built descriptions of divine activity Semantic drift. “Rights” in Japanese canin attachHebrew to governments as different foundations. Additionally, both raise an awkward question: when you translate legal concepts, do they easily as to individuals. Japanese grammar made things harder still. were rendered into more static, predicative stay the same?

Speakers routinely drop subjects when context makes reference clear, forms in Greek,which so downplays that what God does becomes individual agency.

And the elaborate pronoun Scholars have argued about this for decades. Alan Watson thought legal borrowing was easy, pointing to how system bakes relational hierarchy right into speech. Constitutional what God is.

Next we must decide which type of ML to use for the particle classification; supervised or unsupervised.

Supervised models assume that there is a collection of data points for which the target property (particle type) is known, and consists of learning by example through labelling the data. In unsupervised models, no labelled examples exist, and rather than attempting to predict a specific property from the data available, the focus is on discovering patterns in the data. In the case at hand of determining particle type, supervised machine learning is the clear choice. This is the first example of a need for human interpretation and logic in building a valid ML model. Simply chucking your dataset into a ML model will not suffice; purpose-driven choices must be made to ensure that the model accurately yields the desired result.

Within supervised machine learning, several decisions, based on logic and physical intuitions must be made, before one lets the algorithm work its magic. The first step is dividing one’s data for which the particle type is known into a training set, on which one ‘trains’ one’s model, and a testing set, on which one ‘tests’ the just trained model. From this one can go on to apply one’s model to the values for which one doesn’t know the particle types, with a fairly good notion of how well one’s model should perform. The next step is the algorithm itself. While one can technically code one’s own, there are many good preexisting algorithms one can use, coded by others and available to the public. Many of these have parameters that can be set with the aim of achieving a tradeoff between overfitting, where accuracy may be high on one’s training dataset, but it is not generalizable to one’s testing dataset, and underfitting, which is perhaps less accurate on one’s training dataset, but has a better generalization accuracy. One decides the balance oneself when designing a model. One can also determine what one’s model bases accuracy on, i.e. is it the number of misclassified neutrons? Or the number of correctly classified photons? Or some combination thereof?

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Ultimately, as scholars compete for influence and reputation, employing all possible means to fulfil their personal ambitions, most academic work especially in the field of international relations will be formulated in English, or at least another super central or central language [4]. While researching and writing this article, I am aware of the irony of the fact that most of the literature on multilingualism and the hegemony of the English language has been written in English. In fact, the abstract term of “Language” is regularly a signifier for “English” in the literature I employ [8].

In my case, photons and neutrons are getting separated to distinguish between elastic and inelastic scattering, however the majority of the photons are background from the detector itself or the air, and are therefore discarded. In other contexts, photons hold great scientific value where in this case, they are discarded as background information, thereby potentially losing meaningful data. In choosing the specific purpose of a ML model, it is possible that we are losing knowledge of other important physical processes undergone by the ‘background’ photons picked up by the detector. What counts as signal versus noise is never inherent in the translation process, but purpose driven. Machines do not choose these purposes, we do. Translation often involves some type of exclusion, and the meaning we interpret is context dependent. Removing background sharpens one truth, in this case that of the elastic/inelastic scattering incident, while erasing another, the ‘background’ photons. This potential loss of information extends beyond the particle classification case, into any use of ML and AI.

SEL 7

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With the rise in the use of AI, and thereby ML, it is important to maintain a deeper understanding of the fact that machines work differently than humans, and do not have any kind of understanding. While it is easy to acknowledge this intellectually, maintaining a continuously critical approach to all machine-created content presents more of a challenge. That is also why, for example, AI responses to the same problem vary significantly depending on the input prompt. This is seen by many daily with Large Language Models (LLMs), which are a specialized type of ML designed to interpret and generate human language. For example, asking ChatGPT, a popular LLM, ‘Is Groningen the best city for students?’ will 2 more Groningen-positive results than ‘What are the best cities for students?’, which will provide yield a wider overview. LLM’s operate based on past experience, but have no intellect and do not analyse, their answers are purely based on probabilities due to past trends. AI, and under that ML and LLM’s, is only as useful or good as the way in which it is programmed, which is based on the people behind the programming.

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Roman law spread across Europe and common law took root in former colonies. 3 Pierre Legrand disagreed. He language built around autonomous individuals ran into friction at the I am using my Machine Learning model to separate photons and 4 survive because it’s overly tangled up withneutrons, local culture. insisted that legal hoping Then to increase the range of reliable particle grammatical level itself. Today’s revision advocates know all this and If thesemeaning dynamics offails powerto and linguisticstransplantation are so deeply embedded into classification at lower energies. This would open up possibilities academia itself, what can we, as students of the RUG and aspiring academics Gunther Teubner came along with a third option: borrowed rules work like “irritants.”

They provoke reactions, use it, painting the constitution as an alien imposition that encodes to use the same experimental detector setup for new measurements, take from the recognition of these dynamics? which are needed but too challenging at present, and would mean 10 and what emerges is something new, something that surprises everyone involved. 5 This essay takes Teubner’s foreign that valuable data does not need to be thrown away, simply due values. to difficulties in classification.

This highlights the use of ML the idea and runs with it, comparing how Japan and the Baltic states dealt with imposed Western law through in performing data analysis that human logic and statistical If anything, writing this article has helped me to reflect on the conversations I models do not suffice for.

However, because ML does not possess choices theirmight translators made. hold with my roommates, friends, and professors, and how they might understanding, intention, or physical intuition and instead operates purely on statistical patterns, it is crucial to keep in mind that human logic and critical thinking are essential in successfully using AI. ML may help us see what human intuition alone cannot, but only through the collaboration of the algorithm and the developer can ML be successful in producing meaningful knowledge.

advantage or disadvantage them. While many of us are actively profiting from the hegemony of the English language, it is important to understand this privilege not as a welcome coincidence, but a historical and political norm, deeply rooted in the development of the current world order. While the choice of language in official academic and social institutions is always a trade-off between communicative reach and linguistic equality, it might just be worth it to give space to your native language in conversation, and in the choice of language in your future research and academic work. Instead of blindly complying with the norm, our lived realities as students in an international environment should directly challenge the monolingual English bias in research and work.

In 2024, Times Higher education declared the Rijksuniversiteit Groningen to be within the top 30 most international Universities worldwide.

The ranking bases itself not only on the international student score, but also on the international staff and co-authorship score as well as reputation metrics, determining which institutions provide truly international environments for prospective students [2]. This internationality often relies on an important vehicle to enable communication across varying cultural groups: the use of the English language in research, teaching and learning.

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Like many international students studying at the RUG, my relationship to language can be quite complicated. For many, English is a second, third or fourth language that defines much of social and academic life in the Netherlands. In friend groups shaped by different origins and mother tongues, it is the language building From Sarcasm to Illegality Labels and Their Translations bridges, uniting everyone in one conversation and creating fluid discourse without major misunderstandings. Not only is this on a social level, but the opportunities of studying an Lost in Our relevant Age Speaking of another self English taught degree are evident to many, especially when looking at prospects in academic and professional settings. Though its role has become so central in our lives, weBecame rarely Intelligible question the What is a Clock?

When God provenance and the dynamics of this linguistic hegemony that is present on a global level.

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Languages of Power

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Machine Learning

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Borrowed words

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From Sarcasm

to Illegality AI Mistranslation, Hate Speech, and Data Extraction in the Search for Context

By Laura Mairal Sampedro

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I. Introduction: Translation is Never Neutral

Translation, or ‘translatio’ in the Latin language, is fundamentally a reconstruction of meaning from one language system to another, serving as a vital mechanism for crossing physical, intellectual, and cultural boundaries (1). This movement, however, is never neutral; as meaning migrates across these boundaries, it undergoes an interpretative transformation where “perfect equivalence” is rarely absolute (1). In this process, something is inevitably lost, specifically the “cultural depth” of idiomatic expression and the nuanced ‘intended emotion’ that lies beneath the literal surface of speech (2).

Artificial Intelligence (AI) and Neural Machine Translation (NMT) represent a technological attempt to remove this communicative friction, offering ‘language calculators’ designed for maximum time and cost efficiency (3). By treating translation as a codebreaking problem and applying probability-based math models to guess the meaning behind a word, these tools try to make cross-border information flow smoothly and easily, especially on social media (4).

However, the limits of this mechanical approach are laid bare by sarcasm: a sophisticated linguistic act that, intentionally, inverts literal meaning into its opposite (5). Sarcasm serves as a critical boundary case because its interpretation requires a “nuanced understanding” of context and social participation that current automated systems, relying on surface-level keyword spotting and sentiment analysis, are ill-equipped to handle (6).

AI-enabled translation and automated moderation systems reveal that meaning cannot be fully separated from context. When sarcasm is mistranslated as hate speech, interpretative failure becomes regulatory enforcement (7). Efforts to improve translation by data extraction, including harvesting metadata, user history or socio-political network patterns, may ultimately redefine or reinforce the cultural boundaries that translation was supposed to connect and bridge, transforming ‘translatio’ into a tool for mass surveillance (6).

This essay argues that human meaning is a contract relational negotiation that cannot be fully quantified.

By attempting to resolve linguistic opacity through total data extraction, AI risks reinforcing cultural boundaries and subjecting human communication to intrusive algorithmic control.

II. What D oes it Mean to Translate ?

Translation is far more than a linguistic substitution; it is a complex reconstruction of meaning from one language system to another (8). Theoretically, this process is fundamentally interpretative rather than mechanical, demanding a “wide range of intelligence” to reconstruct the value of terms rather than simply identifying their dictionary definitions (9).

Within the framework of hermeneutics, the theory and methodology of interpretation, translation is understood as an act of negotiation deeply embedded in historical and cultural situations (10). This perspective aligns with Walter Benjamin’s view, a highly influential German philosopher who considered translation as the transformation ensuring the “afterlife” of a text (10). Benjamin acknowledges that perfect equivalence is rarely absolute or perfect because meaning is constantly reactivated through local realities and changing identities (10).

The distinction between human and artificial approaches highlights the inherent limits of current technology. Human translation is a creative practice that mirrors the speaker’s intention and emotion, making use of shared cultural knowledge to capture “the hidden parts of the iceberg” (11). Conversely, AI translation operates essentially as a “language calculator” (3). It is built upon stochastic processes and statistical mapping, applying mathematical models to calculate the probability that specific sequences of words will occur together based on patterns in a corpus (14).

While these systems can process massive amounts of data speedily, they often lack the cultural empathy required to understand how meaning is tied to embodied social participation, leading to misunderstanding and cultural insensitivity (1). The difference between mathematical linguistic maps and contextual understanding becomes particularly visible in sarcasm.

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III. The AI’s Achilles heel and Linguistic Failure to Automated Censorship Sarcasm represents AI’s Achilles heel. Artificial intelligence struggles to deepen into the “iceberg’s hidden parts” of sarcasm, where one finds embedded linguistic rhetoric with cultural and political context nuances, all disguised under a twisted intention (5).

Because sarcasm relies heavily on the “common ground” between parties and “shared social norms”, its true meaning is never self-evident in the text itself (12).

Current AI systems, acting as "language calculators”, struggle with this nuanced interpretation because they rely on surface-level lexical analysis (6). While a human can perceive the negative intent behind a positive sentence like “Oh, we live in such a well-run country!”, a machine’s “word-by-word” pattern recognition often fails to detect the underlying political irony: “the country is not properly run by politicians” (5). Without social participation or the ability to navigate the relational context between author and audience, machines remain blind to rhetorical intent (12).

This interpretative failure has immediate human consequences when processed through automated content moderation (14). On platforms like X or Meta, moderation functions as a process of “mechanical translation”, where human expression is reconstructed into machine logic (14). To serve regulatory ends, speech is compressed into probabilistic “emotion scores” and misclassified into policy categories like “toxic” or “hate” (7). In the pipeline, intention becomes irrelevant. Systems prioritize “triggered vocabularies” over rhetorical goals, treating linguistic ambiguity as a statistical threat to be neutralized (15).

The result is a “double translation failure”: the AI interprets a sarcastic expression literally and subsequently applies a regulatory enforcement action (7). For example, a sarcastic remark intended to mock an extremist ideology may be fluffed as a genuine endorsement of that harmful ideology.

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This shift from linguistic error to legal action is further accelerated by intensifying regulatory pressure, such as the EU’s AI Act, which incentivizes platforms toward rapid, cost-efficient removal to ensure compliance (16). In this environment, translation ceases to be an act of communication and becomes a form of risk management, where meaning is lost and sanctioned.

This algorithmic rigidity raises profound freedom of expression concerns, particularly through the disproportionate over-removal of legitimate discourse, especially minority speech and reclaimed language (6). Current models often lack the linguistic intuition to distinguish identity-affirming speech from malevolence (6). For instance, statistics from recent studies on algorithmic bias show that tweets written in African American Vernacular English (AAVE) are two times more likely to be flagged as “offensive” compared to standard English. (7).

Models trained misclassify dialect non-malevolent terms used within minority communities as toxic because their training data lacks dialect diversity (1).

Such systems overlook the wide array of cultural contexts required to understand communication (1).

When a model is “highly sensitive” to offensive tokens but “blind” to rhetorical misdirection, sarcastic resistance is misclassified as harm, resulting in undue censorship (7). While human rights frameworks, such as Article 10 of the European Convention on Human Rights (Council of Europe, 1950), require evaluating a speaker’s intent and historical context, systems prioritize “time and cost efficiency” over such contextual balancing (17). The systems cannot assess subjective intent or evaluate proportionality and, therefore, they lack interpretative safeguards required under human rights law.

The boundary between critique and harm becomes algorithmically established, where interpretive failures are regular, and diverse voices within the digital public sphere are threatened (6). As moderation treats language as a mere “codebreaking” problem, the nuances of free speech are inevitably lost in the migration from human intent to algorithmic enforcement, reinforcing translation boundaries instead of bridging and erasing them.

IV. The Solution: Data Extraction Artificial Intelligence (AI) researchers argue that word-level information, by itself, is insufficient for the system to detect ironic intent deeply rooted in context because the system is limited by the training dataset used (12).. Consequently, automated systems are moving toward a multimodal approach, applying machine-learning systems, requiring significant amounts of data that include not only text but also images, reaction emoticons and audio signals (12).

Modern models increasingly rely on metadata and behavioral signals, such as an author’s historical sentiment, their past topics of interest and “user embeddings” that map their political leanings and personal preferences (12). For example, a user frequently liking Trump’s posts on X above other politicians’ suggests a lower likelihood that the user’s political sarcasm is meant to oppose him. By integrating data from cross-platform sources like Meta, X and Flickr, these systems attempt to establish the “relational context” and “common ground” that humans use to perceive irony (12).

Eventually, the system builds a popular neuronal network architecture (12).

This technical shift reveals a fundamental truth: to translate culture, AI must harvest culture (13).

Systems no longer simply process words; they must ingest the “hidden parts of the iceberg”.

Nonetheless, the need for deeper contextual understanding creates a profound legal and ethical tension with Regulation (EU) 2016/679 (2016) principles, particularly the mandate for data minimization (19). While users often expect their data to be deleted after a translation is performed, providers frequently engage in “secondary processing”, keeping and re-using input data to improve the translation model, or for commercial purposes (19).

The more these systems seek contextual integrity, the more they require a deep intrusion into personal life, capturing everything from location data to private interactions (19). Ultimately, translation becomes extraction.

While translation should aim at removing “the veil of opacity” a non-translated text has for a foreign reader, AI’s application does not bridge this linguistic gap but turns everyday communication into mass surveillance (4).

In conclusion, in order to “solve” the problem of sarcasm, AI systems must abandon the principle of data minimization in favor of mass surveillance.

While such practice may refine an algorithm’s ability to detect irony, the social and legal harm of such extraction far outweighs the benefit of more accurate text classification.

V. Boundaries: Protection or Obstacle ?

Within the intersection of Sarcasm and surveillance, boundaries function as both a necessary shield and a restrictive barrier. In the first typology, cultural communities preserve internal nuance through shared norms and local realities that exist beneath the literal surface of speech (10). Likewise, legal systems provide interpretive safeguards through frameworks like Article 10 of the ECHR, which require the evaluation of subjective intent and proportionality (17). Privacy laws, such as the GDPR, further protect the integrity of the self by limiting the “translation through extraction” that defines the business models of surveillance capitalism (19).

On the other hand, boundaries simultaneously serve as obstacles to cultural interchange and technological optimization of digital translators. They slow progress by restricting access to the vast, multimodal datasets required and the training of neural architectures (19). Scarcity of labeled datasets for complex linguistic phenomena like sarcasm prevents models from mastering the “hidden parts of the iceberg”, leading to significant “double translation failures” where meaning is actively sanctioned (5).

Consequently, a profound tension arises: boundaries simultaneously protect meaning and constrain translation (4). By resisting the total conversion of human experience into standardized, machinereadable data, these limits preserve the “cultural empathy” required to ensure we still “speak Human” in an automated age (4).

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VII. Conclusion: The Limits of Translation Translation ultimately reveals that meaning is relational, existing not as a static, extractable data point but as a constant “negotiation” between individuals rooted in specific local realities and changing identities. While AI attempts to reduce human interaction to mathematical modes and statistical mapping, the boundary case of sarcasm demonstrates that context cannot be fully reduced to data.

Human communication thrives on a degree of social ambiguity, where emotion, social identity and intent freeze all together in the hidden parts of the iceberg. The emotion comparison systems and language calculators cannot perceive this linguistic ambiguity.

The technical drive to “remove the veil of opacity” through total data extraction ignores the fundamental truth: a perfect equivalent is rarely absolute. To truly “speak human” is to engage in this negotiation of words’ meaning and interpretation instead of mechanically applying language datasets.

Sarcasm resists computational translation not because machines are insufficiently advanced, but because meaning depends on shared worlds that cannot be fully extracted or quantified. In seeking to perfect translation, AI systems risk flagging prompts as hate speech and extracting personal data, reinforcing boundaries instead of bridging them.

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[XVIII Seminario Aiclu] International Conference, Napoli, Italy. https://usienaair.unisi.it/handle/11365/1257017?mode=simple 4 Cronin, M. (2013) Translation in the Digital Age. Taylor & Francis Books. https://doi.org/10.4324/9780203073599 5 Liu, P. et al (2014). Sarcasm Detection in Social Media Based on Imbalanced Classification. In Li, F. et al (Eds.), Web-Age Information Management. (pp. 459-471) Springer https://doi.org/10.1007/978-3-319-08010-9_49 6 Mamun, M.B. et al. (2024). Sarcasm-Aware Hate Speech detection using Rationales [Doctoral dissertation, Shizuoka University. https://www.researchgate.net/publication/385318646_SARCASM-AWARE_HATE_SPEECH_DETECTIO N_USING_RATIONALES 7 Mamun, B. M. et al (2024). Hate Speech Detection by Using Rationales for Judging Sarcasm. Applied Science MDPI, 14, 1-19. https://doi.org/10.3390/app14114898 8 Catford, J.C. (1965). A Linguistic Theory of Translation. London: Oxford University Press.

9 Klein, H. K., & Myers, M. D. (1999). A Set of Principles for Conducting and Evaluating Interpretive Field Studies in Information Systems. MIS Quarterly, 23(1), 67–93. https://doi.org/10.2307/249410 10 Demeke, W. and Ryan, B. (2021). Lost in translation: Qualitative Data Collection and Translating Challenges in Multilingual Settings in Information Systems Research. University of Dar es Salaam Library Journal, 16(2), 105-18. https://journals.udsm.ac.tz/index.php/lj/article/view/4520

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11 Magiera-Gaszynska, M. (2018). Is it Possible to Translate What Is Not Said? The literary translation and the Ice-berg cultural model. Studia Iberystyzcne, 17, 273-286. https://doi.org/10.12797/SI.17.2018.17.18 12 Amir, W. et al,. (2016). Modelling Context with User Embeddings for Sarcasm Detection in Social Media. In Riezler, S. and Goldberg, Y. (Eds.) Proceedings of the 20th SIGNLL Conference on Computational Natural Learning (pp. 167-177). Association for Computational Linguistics https://aclanthology.org/K16-1017/ 13 Sharma, D.K. et al. (2022) Sarcasm Detection over Social Media Platforms Using Hybrid Auto-Encoder-Based Model.

Electronics MDPI, 11(8), 1-20. https://www.mdpi.com/2079-9292/11/18/2844 14 Alqohfa, K.A.S and Sanad S.N.T. (2025) Linguistic and Cultural Challenges in Translating Idioms with Artificial Intelligence.

Journal of English Studies in Arabia Felix, 4(1), 34-49. https://doi.org/10.56540/jesaf.v4i1.116 15 Meriem, B., Hlaoua, L. and Romdhane, B.L. (2021). A fuzzy approach for sarcasm detection in social networks. Procedia Computer Science, 192, 602-611. https://doi.org/10.1016/j.procs.2021.08.062 16 EU Parliament, (2018, 2021) Coordinated Plan on Artificial Intelligence. https://digital-strategy.ec.europa.eu/en/library/coordinated-plan-artificial-intelligence-2021-review 17 Council of Europe. (1950). European Convention on Human Rights. https://www.echr.coe.int/documents/d/echr/convention_ENG 18 European Parliament and Council of the European Union. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation).

Official Journal of the European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/? uri=CELEX:32016R0679&qid=1685451198313 19 Kamocki, P. and O’Regan, J. (2016). Privacy Issues in Online Machine Translation Services - European Perspective. European Language Resources Association (ELRA), 4458-4462. https://aclanthology.org/L16-1706/

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Lost in Our Age: When Confusion Learns Compassion trading cards and time, in a language we didn’t yet know

By Hidde Nijenhuis

the distance between us is quiet. there wasn’t a door that slammed. no final words or goodbye. no moment to point to and say, “there, that was it.”

just two kids standing on opposite sides of a slowly widening Sunday afternoon. back then we measured time in Pokémon cards on the living room floor, in the soft clicks of our Nintendo controllers, in the blue glow of a 6-inch landscape screen long past when we were meant to sleep. in your voice saying my name once, then twice, so I would look up and stay.

I didn’t notice when the air between us started changing dialect, how silence could grow legs, how pride could wear the mask of the busy, and how hurt, when it’s young, doesn’t know where to sit. but you kept knocking gently, sending photos, messages, “hey, u free?”, like folded footnotes sliding under a door I don’t remember closing.

8

I thought the story then was about my missings, how your house felt bigger than mine, and your family was together most of the time. how your world looked steadier like one of those games that never seemed to glitch no matter the screentime. how your life, from where I stood, seemed to keep moving, improving, unwavering. it’s strange how memory translates with time. the same moment, years later, speaking in a softer accent.

because now, with quieter hands and a heart that startles less easily, I can see you there. just a kid trying in the only language he knew, offering distractions like bandages, pressing small joys into my hands as if fun itself might keep the hard things from spilling over. standing in the soft confusion of being 14, wanting things to just be okay again. not oblivious. not a bystander. not the apathetic I drafted in my head.

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twice a , once or sometimes isits me. a scent v

year,

ery time.

I stop ev isle. grocery a ate. g t r airpo . important somewhere .

I’m late damn it, nocking, without k t n e s e r p he through t in. it slips small aga m a I y l n e d d u and s s car, your mom’ f o t s, a e s k c he window in the ba ng past t i r ng ahead, r i u z l z b u b m nament r Amsterda u o e. t n o m Poké ng to nam e too you our first r e w e w e omis ut like a pr ves witho lgia arri a t yscale of s a o r n g l e a ugh th at nas o h r t h t n e e h u w l b and ring n, flicke me permissio wn beside o d s t i s d n a today, , ever left like it n . y sta e, I let it l the tim ut you al o b a k n i h I t ents. ssing mom in the pa o slowly, it lands, little to a s d a o ake sure l m n o e t e r e c c s i me tw , and the when a says a na f nowhere o e n t o u e o m o y s b when st. drifts rd the pa eme song htly towa g i when a th l s o s s ever room tilt

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that is what time does. it rewrites the feeling without changing the facts.

I still play sometimes, not the way we used to. carefully now. because the cards are the same, but the deck reads differently when you're the only one still playing. you were my friend, but I was a kid with too much weather in my chest. and somewhere in the space between those two truths, we missed each other by inches.

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DECENTERING WESTERN NORMS IN GLOBAL PSYCHOLOGICAL TESTING By: Janine Brouwer 12

OVERVIEW OF PSYCHOMETRIC TOOLS Most clinical psychological tests and instruments have been developed in North America. The most famous cognitive tests, such as the Weschler Scales, StanfordBinet test, and Vineland Adaptive Behavior Scales (VABS), were developed in the U.S.A. The most popular personality tests have also originated from there, for instance the Minnesota Multiphasic Personality Inventory-2 (MMPI-2), NEO Personality Inventory (NEOPI), and 16 Personality Factor Questionnaire (16PF) [1]. Most of these tests have near-perfect reliability and validity, hence their popularity in clinical use.

As a consequence, researchers outside the U.S.A. have translated them into different languages with varying degrees of success.

TRANSLATED INSTRUMENTS Referring back to the case of W.M., several psychological tests have been translated to Arabic.

However, nearly 80% of instruments translated from English to Arabic do not comply with standards of test development. Furthermore, the validity, reliability and psychometric properties of such instruments is hardly reported, or poor [2]. This finding is a hindrance to research emerging from psychological studies conducted in Arabic. In fact, while the number of publications concerning psychological tests has increased since 2010 in the Arab world, nearly half of them do not

employ cognitive tests that comply with international guidelines [3]. Similar issues are observed in instruments translated into other languages. For instance, a study found strong statistical and methodological limitations in the development and use of the Spanish translation of the WISC [4]. The use of inadequate cognitive instruments in Spanish is particularly worrisome, as it is the fourth most-spoken language with approximately 500 million native speakers. When directing the scope of examination towards personality tests, similar problems arise. For instance, the validity scales of a Korean translation of the MMPI-2 did not have a significant advantage over the original instrument, when tested among Korean-native speakers [5]. It maybe deduced that the translation failed to fairly represent the items to test-takers.

Subsequently, rather than outperforming in their native Korean, they instead obtained similar results as in a less familiar language. This is troublesome in self-reported instruments, such as the MMPI2, where the administrator is to abstain from helping the participant.

These findings indicate substantial issues in non-English speaking settings, as inadequate psychological tools seem to be affecting both clinical practice and research in the field. The former can lead to misdiagnoses, whereas the latter perpetuates false beliefs and misconceptions. There needs to be true cultural adaptation, rather than mere translation.

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CULTURAL VALIDATION

DIALECTS AND

OF ORIGINAL INSTRUMENTS

BILINGUALISM

A result of translated scales being often inadequate is some professionals using the original instruments when their patients are fluent in English. However, even the original versions of the tests present significant cultural biases that can impede proper diagnoses, treatments, and research.

For instance, the MMPI-2 has been shown to wrongly pathologise Indigenous peoples, specifically belonging to the Eastern Woodlands Nation in Oklahoma. Their worldviews, culture, and behaviors are perceived as maladaptive due to the test’s norm on WEIRD (Western, Educated, Industrialized, Rich, and Democratic) people.

Consequently, some Indigenous peoples have been misdiagnosed with a certain disorder when they either have another or none at all [6]. This finding is especially concerning because the group studied was fluent in English, controlling for linguistic disadvantages. With regard to neuropsychological tests, cultural discrepancies are heavily present too. Native English speakers residing in the U.S.A. with Latin-American descent, also tend to score poorer than their WEIRD counterparts on cognitive tests [7]. Cultural beliefs, constructs, and values are not addressed or taken into account by test developers, which can alienate many testtakers [8]. The problem is not only linguistic equivalence but construct equivalence.

What further complicates the matter is the difficult and tedious task of adapting psychological instruments to local dialects. In countries, such as South Africa, translating a psychological tool fairly would have to be done eleven times to account for all the dialects. One such dialect is Tshivenda which unfortunately failed reliable and valid translation attempts of the 16PF [9]. Due to large numbers of dialects, difficulty in finding licensed translators and relatively few speakers, many researchers are discouraged from taking on this challenge. As a consequence many dialect speakers, such as W.M., obtain either distorted results or do not have the proper tools with which to be assessed. A popular alternative is to use instruments in another language, as dialect speakers can be bi/polyglots. However, research has shown that bilinguals or polyglots often respond differently to instruments, depending on which language they are administered in. For example, a study conducted on people fluent in both Swedish and English, revealed that their personalities differed significantly when taking the Big-5 Inventory (BFI) in both languages.

Participants rated themselves as more agreeable and conscientious when filling out the BFI in Swedish, whereas they appeared more extroverted when filling it out in English [10].

These findings raise concerns about the use of psychometric tools with bilingual individuals.

The general consensus is that such tests should be administered in the language the participant is most comfortable with, but there is no standard on how to choose a language when they are equally comfortable with several

STRUCTURAL OBSTACLES Adapting original instruments into other languages is a long and tedious task. One of the main issues that hinder the development of such tools is lack of funding.

For instance, an analysis showed that the entire African continent receives less than 0.65% of global research grants [11]. Whereas in Latin America, Brazil is the only country to invest more than 1% of its GDP on development and research [12]. As a result, lower financial support encourages researchers to take up additional jobs (teaching, mentoring, etc.) to cover their expenses, or to seek opportunities elsewhere.

These constraints may contribute to a reduction in quality or quantity of research produced, which could explain why translated instruments do not always meet international standards.

Another issue could be the time constraints that instrument adaptations impose. A meta-study in Greece attempted to adapt 17 psychological instruments from English to Greek, to enhance mental welfare for children and adolescents. The cross-cultural adaptation method has 6 lengthy steps, involving several panels of experts, translators and community representatives [13].

Unsurprisingly, one of their listed limitations is time constraints, and difficulty in meeting deadlines. Hurrying the adaptation process may negatively impact the outcomes. If the design of instruments in new languages is excessively rushed, they may lack validity and reliability.

Lastly, journals frequently decide against publishing articles on adaptation of psychological tools. In fact, recent research has pointed out that publishers are not interested in psychometric adaptations of scales and instruments [14]. Consequently, researchers are discouraged from creating adapted tools, or are unable to share their findings

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with the rest of the academic community. This not only leads to overall lower interest in these matters, but also less uptake of such instruments by the clinical world. Creating an instrument in another language, just for it not to be clinically considered due to publishing differences, is akin to having an answer to a problem but being unable to share it.

THEORETICAL FRAMINGS One of the setbacks to crosscultural test adaptation is the positivistic paradigm in psychology. This view favours quantitative, observable and empirical data. Due to its strong emphasis on concrete and discrete variables, it often misrepresents or excludes culture altogether.

And when culture is examined, it is taken to influence the strength Western constructs, rather than re-examine the constructs altogether [15].For instance, the positivist paradigm could argue that Syrians are more agreeable, according to the NEO-PI, rather than redefining agreeableness from Syrians’ perspective.

Thus, people of various cultural backgrounds are examined from a western-focused view, dismissing their potential differences [8].

Within psychometrics, this manifests in the pursuit of measurement invariance; the assumption that psychological constructs are equivalent across populations, thus measurable through standardized instruments.

Cultural differences are often treated as deviations from established norms rather than as opportunities to reconsider the constructs themselves. A key issue here is the use of the etic (outsider) perspective, which encourages objectivity and scientific analyses. In a culturally adaptive context, the emic (insider) approach would be

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much more constructive, as it aims to understand ideas from the interlocutor’s perspective [16].

An alternative paradigm would be critical psychology. This school of thought opposes positivistic, WEIRD, and capitalistic methods of studying psychology. It posits that truly inclusive research should acknowledge the frameworks within which it exists, rather than assume that it is applicable in all contexts.

Critical psychology argues for the recognition of power imbalances, societal injustices, and historical mistreatment of marginalized groups. By doing so, it places culture, and its intersections, at the center of research through an emic lens.

From this perspective, the dominance of Western psychometric instruments reflects asymmetries in research funding, publication practices,and institutional authority. Cultural misdiagnosis, therefore, is not only a technical issue but also an ethical and political one.

Unlike positivism, critical psychology gives a lot of significance and meaning to cultural differences.

As a result, cultural differences are recognised, rather than ignored for the benefitof westerninstruments [17]. By integrating emic approaches and critical awareness into assessment practices, psychologists can move toward instruments that are not only linguistically accurate but culturally meaningful. Such a shift does not require abandoning scientific rigor; rather, it demands expanding the definition of rigor to include cultural reflexivity and contextual sensitivity.

RECOMMENDATIONS Most psychological scales adaptation include the five following steps: instrument translation, synthesis of the translated versions, examination of the synthesized version by experts, back translation, and a pilot study.

However, researchers argue that including an evaluation by the target population is a crucial step in instrument creation.

By inviting community representatives to give feedback on tools, cross-cultural adaptation deepens.Another major step should be statistical analysis, by using exploratory and confirmatory techniques. Including such a measure would ensure higher validity, reliability and ease the transition of the instruments to clinical settings [18]. Culturally valid assessment enables culturally responsive treatment.In fact, there are many benefits to using culturally adaptive instruments.

Cognitive behavioral therapy (CBT), is a clinical technique for treating various psychological disorders, popular amongst practitioners and patients alike.

Culturally adaptive CBT (CA-CBT) employs similar techniques and methodologies, whilst encouraging inclusion and recognition of cultural differences. CA-CBT has been shown to be more effective than traditional CBT in reducing the symptoms of depression among Chinese-Americans, and symptoms of PTSD among Syrian refugees. It also seems promising in treating diverse populations such as Afghan refugees and Jordanian children [19].

Overall, psychologists are recommended to implement culturally adaptive practices in both research and practice.

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FUTURE DIRECTIONS AND CONCLUSION The case of W.M. is not isolated nor unique. There are many such individuals for whom adequate psychological tests are inaccessible. This is due to a plethora of reasons including: statistically lacking translated scales, culturally insensitive original instruments, limitations in dialects test development, and caveats in bilingual testing.

Countering such issues and addressing structural obstacles are the first steps towards creating inclusive testing. However, the road to true and full inclusion is long, and paved with dilemmas and uncertainties. For instance, with limited resources is it more essential to fund the creation of scales in a new language, or the adaptation and translation of original instruments? To what extent should the knowledge and wisdom of local populations, rather than psychological experts, guide the development of scales? Researchers can expect to encounter such issues, as they investigate and produce culturally adaptive instruments. While no universal solution exists, the ethical responsibility to prevent cultural misdiagnosis remains clear. Psychological assessment carries strong consequences for educational placement, clinical treatment, and life trajectories.

When instruments fail to account for linguistic and cultural context, they risk misrepresenting the very individuals they seek to understand. Everyone should have equal access to accurate psychological assessment.

No one’s perceived intelligence should rely on the language in which a “clock” has to be defined.

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REFERENCES [1] Hogan, T. P. (2018). Psychological testing: A practical introduction (4th ed.). Wiley.

[2] Zeinoun, P., Iliescu, D., & El Hakim, R. (2022). Psychological tests in Arabic: A review of methodological practices and recommendations for future use. Neuropsychology Review, 32, 1–19. https://doi.org/10.1007/ s11065-021-09476-6 [3] Fasfous, A. F., Al-Joudi, H. F., Puente, A. E., & et al. (2017).

Neuropsychological measures in the Arab world: A systematic review.

Neuropsychology Review, 27, 158–173. https://doi.org/10.1007/s11065-0179347-3 [4] McGill, R. J., Ward, T. J., & Canivez, G. L. (2020). Use of translated and adapted versions of the WISC-V: Caveat emptor.

School Psychology International, 41(3), 276–294. https://doi. org/10.1177/0143034320903790 [5] Ketterer, H. L., Han, K., Hur, J., & Moon, K. (2010). Development and Validation of Culture-Specific Variable Response Inconsistency and True Response Inconsistency Scales for Use with the Korean MMPI-2.

Psychological Assessment, 22(3), 504–519. https://doi.org/10.1037/ a0019511 [6] Hill, J. S., Pace, T. M., & Robbins, R. R. (2010). Decolonizing personality assessment and honoring indigenous voices: A critical examination of the MMPI-2. Cultural Diversity & Ethnic Minority Psychology, 16(1), 16–25. https://doi.org/10.1037/a0016110 [7] Rosario Nieves, E., Rosenstein, L. D., González, D., Bordes Edgar, V., Jofre Zarate, D., & MacDonald Wer, B. (2024). Is language translation enough in cross-cultural neuropsychological assessments of patients from Latin America?

Applied Neuropsychology: Adult, 1–12. https://doi.org/10.1080 /23279095.2024.2376829

[8] Fetvadjiev, V. H., & van de Vijver, F. J. R. (2015). Measures of personality across cultures. In G. J. Boyle, D. H. Saklofske, & G. Matthews (Eds.), Measures of personality and social psychological constructs (pp.

752–776). Academic Press/Elsevier. https://doi.org/10.1016/B978-0-12386915-9.00026-7 [9] van Eeden, R., & Mantsha, T. R. (2007). Theoretical and Methodological Considerations in the Translation of the 16PF5 into an African Language. South African Journal of Psychology, 37(1), 62–81. https:// doi.org/10.1177/008124630703700105 [10] Dylman, A. S. & Zakrisson, I. (2025). The Effect of Language and Cultural Context on the BIG-5 Personality Inventory in Bilinguals.

Journal of Multilingual and Multicultural Development, 46(2), 392–405. https://doi.org/10.1080/014 34632.2023.2186414 [11] Nabyonga-Orem, J., Asamani, J. A., Nyirenda, T., & Abimbola, S. (2020). Article processing charges are stalling the progress of African researchers: A call for urgent reforms. BMJ Global Health, 5(9), e003650. https://doi.org/10.1136/ bmjgh-2020-003650 [12] Uskul, A. K. (2024). Challenges and opportunities for psychological research: Limited funding and institutional support in crosscultural contexts.

Collabra: Psychology, 10(1), Article 123703. https://doi.org/10.1525/ collabra.123703 [13] Karagiorga, V. E., Schafer, J. L., Marchionatti, L. E., Caye, A., et al. (2024). Translation and cross-cultural adaptation of seventeen widely-used assessment instruments for child and adolescent mental health in Greece. Journal of Patient-Reported Outcomes, 8, Article 18. https://doi.org/10.1186/s41687024-00693-0

[14] Vitoratou, S. (2017). A note on contemporary psychometrics: What journals publish and what they don’t.

Disability and Rehabilitation, 39(9), 919–925 https://doi.org/10.1080/0963 8237.2017.1392008 [15] Ratner, C. (2008). Contextualism versus positivism in cross-cultural psychology. In G. Zheng, K. Leung, & J. G. Adair (Eds.), Perspectives and progress in contemporary crosscultural psychology: Proceedings from the 17th International Congress of the International Association for Cross-Cultural Psychology. https:// doi.org/10.4087/QURX7615 [16] Mostowlansky, T., & Rota, A. (2023). Emic and etic. In F. Stein (Ed.), The open encyclopedia of anthropology. Facsimile of the first edition in The Cambridge encyclopedia of anthropology. http://doi. org/10.29164/20emicetic [17] Teo, T. (2021). History and systems of critical psychology.

Oxford Research Encyclopedia of Psychology. https://doi.org/10.1093/ acrefore/9780190236557.013.663 [18] Borsa, J. C., Damásio, B. F., & Bandeira, D. R. (2012). Crosscultural adaptation and validation of psychological instruments: Some considerations.

Paidéia (Ribeirão Preto), 22(53), 423–432. https://doi. org/10.1590/S0103-863X2012000300014 [19] Gkintoni, E., & Nikolaou, G. (2024). The cross-cultural validation of neuropsychological assessments and their clinical applications in cognitive behavioral therapy: A scoping analysis. International Journal of Environmental Research and Public Health, 21(8), 1110. https:// doi.org/10.3390/ijerph21081110

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Labels and their translations how museum texts shape visitors’ experiences By: Zofia Skwarzyńska

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INTRODUCTION In 2019, the International Council of Museums (ICOM) announced that museums can be defined by transparency and participation, as they rely on diverse communities and cultural groups collaborating in order to display, preserve and promote understanding of the world as we know it [1] . In order to achieve that, translation is deeply needed on both linguistic and cultural level. And one of the most significant texts in the museum environment which influences the perception of exhibited objects, is a text label. Museums, as physical spaces providing presentation of culture, are places in which translation plays a key part. However, it is not only the interlingual translation of texts, for people of various lingocultural groups, but also cultural translation, which affects both national and international visitors. Cultural translation enables the creation of representation for people who are more familiar with the sociocultural contexts, as well as for those who are unaccustomed to the topic. Therefore, interlingual translations often differ from the original text, as non-native speakers might not be aware of cultural or social contexts, resulting in certain additions or vast changes being implemented. It is also important to consider how text is translated and presented within the space itself, as the exhibition can be understood as a text of its own, where objects, visual art, sound and writing relate to one another, whether intrasemiotic or intersemiotic.

The way artworks are displayed in the designated rooms, and the manner in which they interact with the accompanying information plaques or other juxtaposed artworks is significantly interconnected.

This is not a display of separate elements, but rather a well-considered interplay between all segments [2, p. 159]. The case study of Who writes History? exhibition at the Groninger Museum presented in this essay focuses on the intrasemiotic correlation between the Dutch wall-text and its English translation, as their arrangement varies greatly and consequently impacts visitors’ experiences, depending on their cultural and linguistic backgrounds. It is important to note that further research on translation in museum environments has been suggested by Robert Neather

in the Handbook of Translation Studies, particularly with regard to how they are being perceived by visitors from different backgrounds, and to what extent they can influence one’s perception of the exhibition [2, p. 163] . The following essay presents contemporary methods and research, together with the author’s own experience at the Museum aan de A’s guest exhibition at the Groninger Museum. The objective is to encourage future visitors to pay more attention to labels, their translations, arrangement and impact on one’s experience.

METHODOLOGY The methodology is based on both quantitative and qualitative research, involving a site visit, document analysis of books and articles, and a case study of the Museum aan de A’s guest exhibition Wie schrijft geschiedenis? (Who writes History?) at the Groninger Museum, with a focus on two selected labels featured in the exposition space. The methodology of the research is predominantly grounded in geosemiotics, a theoretical framework which examines public discourses in a spatial setting. The meaning of signs, logos and short texts is analysed within a physical and social context. The two case study labels of the exhibition will therefore be assessed not only by their visual semiotics, but also their placement in the exhibition space and their reception. The focus of this short essay will be on emplacement, which refers to the physical placement of the labels, code preference, which is the chosen language, and inscription, being the presentation of Dutch labels and a comparison with the English ones [3, pp.

63, 67, 70, 71].

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WHAT IS A LABEL?

TRANSLATION IN

Usually, the term label refers to surfaces in the form of cards, plaques and wall texts, which function as guides providing information on the exhibition and the objects one can find in a museum space.

The information may be a general overview of the exhibition or a detailed description of a specific object or artist. They are most frequently displayed as short sentences or comprehensive paragraphs. The majority of the texts are designed to guide the visitors through the exhibition, highlighting the most important aspects the readers should be aware of in the particular museum setting [4, p. 14].

MUSEUM SPACES

In the following essay the term label is employed to signify a specific type of a wall text, as well as texts written on a flat surface within the exhibition space, which are designed to be engaged with by writing one’s opinions and remarks. In both arrangements, the labels provided factual information (translated as facts) and asked questions about the visitors’ own ideas or interpretations (translated as thoughts).

Therefore, the labels functioned as an interactive tool in the exhibition space. In the following text, the term “Dutch labels” will refer to the original texts, while the “English labels” will refer to their English translations, which are displayed in a different manner.

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Museums have been making a significant amount of progress in their efforts to engage visitors with labels, offering a more enjoyable and educational experience. This is often achieved through the utilisation of creative text labels, which are read by visitors and thus allow them to interact with the artworks in the exhibition. It is important that the labels encourage visitors to approach them, start and finish reading the information, as well as remember the content of the texts, in order to later contemplate the artworks and the exhibition from a different perspective.

What is more, a conversational type of text is considered more engaging due to their interactive nature which is easier to follow [5, pp. 2, 11] . This sense of inclusion and accessibility has been curated in the exhibition at the Groninger Museum. The use of dynamic arrows, diverse fonds, varied sizes, as well as strategic placement and distribution of texts creates a visually dynamic experience that successfully engages the viewer.

Regarding the translation of such labels, the way they are presented is quite relevant, given that international visitors may have different cultural and social knowledge, which can affect the experience of interacting with artworks and texts. It is therefore important to consider what should be translated and by what means.

Which elements should be added or removed, and how can the English text be made accessible to various heterogeneous groups from different countries, so that each group feels included and not overwhelmed by the language, as the expectations and English skills might differ from group to group? Moreover, it is significant to note that the process of translating museum objects and themes should always be considered with the artworks in mind.

“

In the case of the essay on Who writes History? exhibition, the focus is on representational and organisational aspects. It becomes quite visible how the Dutch and English labels differ in terms of text and elements incorporated into the translation, which is considered the representational framework, and the way in which the labels are displayed, being the organisational framework.

It is an unfortunate strategy to omit the object of interest, as the translator should not only focus on the pure linguistic aspect, but also on the cultural one

“

“

“

,as the way viewing a work of art or its environment might have a different effect on national and international viewers [4, pp. 15-16] .

It is noteworthy that museum texts are written in a way that ensures they do not overbear visitors with the great amounts and challenging type of information.

In order to make sure the audience understands the topic of the display, it needs to be considered what type of text is able to support all necessary information, and that there is space dedicated for one’s own interpretation and reflection [2, p. 162] .

The idea of not overwhelming the reader with excessive paragraphs is also of importance for the process of text translations. In the context of exhibition spaces, translation does not necessarily give different information from the source text, which would be the official label.

Instead, it is a functional tool to showcase to international visitors what is written and therefore deemed significant for the exhibition. Therefore, the function of the source and the translation should be equivalent.

One should not forget that not only labels, but also the entire space of a museum exhibition should facilitate an inclusive environment, where the amount of information and spatial design correlate to each other, providing educational and social purposes. This is the reason why museums often opt for less formal displays, allowing the expression of the inner homo ludens during the visit.

Moreover, exhibitions function as a space through which different interpretations are invited, as the curation of an exhibition can influence the visitors’ understanding, particularly when referring to an international audience [7, pp. 1, 4] . The exhibition at the Groninger Museum fulfils such a purpose, creating an environment where visitors directly engage with the space, fostering a sense of participation in a big project. They can write their personal opinions and ideas about the exhibition itself, or the general topic on museums.

Nevertheless, translations often differ from the source text in order to accommodate the needs of visitors who may not be aware of linguistic, social or cultural nuances found in the original text [6] .

Accordingly, the three main frameworks (representational, interactional and organisational) of all museum texts should also be taken into consideration while in the course of translation.

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CASE STUDY: WHO WRITES HISTORY? The temporary exhibition at the Museum of Groningen occupies a relatively small space, giving the impression of a real place where museum objects are being stored. The exhibition consists of one primary room and two additional areas, which all collectively display the significant artefacts of the province’s history and contemporary context. The exhibition provides insight into the objects that will be shown in the Museum aan de A, which has not yet opened its doors to the public. The exposition further explores the main question of who exactly has an impact on museums and what they display. The blueprint walls indicate the construction is ongoing. Furthermore, all objects are systematically numbered, which gives the viewer the opportunity to imagine themselves in the role of a curator or museum staff member. Visitors are encouraged to answer questions on a board with magnetic points or to even write their thoughts and opinions on a white blueprint, which is situated on a large table that also displays numerous artworks.

This offers a sense of being a part of the project, the level of involvement, and the feeling of being heard and seen.

Interestingly, the idea of

“post-museum” introduced by Eilean Hooper-Greenhill Post-museum - a term introduced

by Eilean Hooper-Greenhill, which concerns a museum model that prioritises the experience of people from various backgrounds, in order to organise interdisciplinary exhibitions that actively engage the visitor with a range of cultural and artistic activities.

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a museum theorist who emphasises the role of the exhibition space as a safe environment for collaboration and community engagement, can be seen in the exhibition Who Writes History?, as well as in the broader mission of the Museum aan de A. The exhibition showcases the museum’s mission, allowing visitors to connect while exploring the history and themes of the city and province of Groningen. The exhibition enables each visitor, regardless of their language or cultural background, to contribute to the curation of objects and organisation of activities [8] . The inclusion is achieved by numerous texts and questions, which not only stimulate visitors’ reflection, but also allow them to write a short text or choose an existing option. The cultural exchange and inclusion of visitors who do not speak Dutch is provided by the translations of both facts and thoughts. In that way, international visitors are encouraged to articulate their remarks, which are later taken into consideration, along with the texts written by national visitors.

Regarding the organisational framework, the English labels appear in the form of a densely compacted text appearing beneath a line, serving as the visual indicator that the viewer is now looking at the English written label. The text is positioned at eye level and has a smaller font size than the Dutch labels. The font remains consistent throughout the whole text. Two words, fact and thought, are written to distinguish the two aspects. The label thus comprises a form of inclusion for non-Dutch speakers, aligning with the museum’s mission to include diverse visitors.

The fact that Groningen is an international city is also relevant in the appearance of such English texts. The label is displayed in a single space on the wall or table, ensuring that the viewer has access to the information in one place. This is also due to the fact that the sentences are written close to each other as one unified text.

The Dutch labels look vastly different from their English counterparts. The fact and the thought are distinguished by a different font and size of the letters, so there is no need to write the two words, as it is assumed the viewer will understand the different functions of the texts. Not only is the fact distinguishable through the fond,

but also by the informational character of the text, while the thought mainly consists of questions for the reader. Additionally, the arrows guide the reader through the texts, starting with examining the object, then moving to the fact, and finally concluding with the thought. The latter is the most eye-catching with its size, distinctive font, and saturated yellow colour, the same one used with the arrows. Thus, the display seems less formal in comparison to the English texts. The labels demonstrate how museums nowadays adapt to the new needs, focusing on the conversation between the curator and the visitor, as the latter is drawn to the text. This suggests that the curators prioritise visitors’ ideas and thoughts, which is consistent with the premise of the exposition to concentrate on their contribution. While comparing the Dutch and English labels, it is revealed that the Dutch speakers’ opinions and experiences are placed at the centre, as the Museum aan de A focuses on the city and province of Groningen, where Dutch is the official language [9] .

Considering emplacement, the English texts are less visible than the Dutch ones.

This is primarily due to the visual design, as the English labels look more condensed and have a smaller font size. However, due to that difference, they are easy to identify by non-Dutch speakers, who upon reading the first label are able to find the necessary information during the entire exhibition.

In terms of code preference and inscription, the Dutch labels occupy the central space, therefore being more visible and easier to interact with, contributing to the sense of place. The significance of translation in museum labels is considerable, as

it gives an opportunity to connect individuals from various cultural and linguistic backgrounds.

It is important to remember, however, that linguistic translation is interdependent on visual experience in the exhibition space.

The texts always refer to the subject of the

exposition, the objects or the artist. Therefore, the translated texts influence how visitors perceive the artworks, in an analogous manner to the Dutch labels.

It is important to consider which cultural and linguistic aspects might not be known by international visitors, and how to present them without excessively changing the primary text [10] . The presentation of such information in the translated text is visible in two examples from the exhibition.

The first one is a text label for Portrait Beetke Aylkema van Rasquert by an unknown artist, a Renaissance portrait displaying Beetke Aylkema van Rasquert with a dog in a frontal pose. The woman embodies a sense of authority and knowledge, gazing at the viewer sternly with her hand on a book. The landscape to her left is of equal significance. There, the ruins of borg Ewsum are clearly visible, which is indicated by the information on the wall label. The Dutch text states “Op de achtergrond zie je de ruïnes van borg Ewsum, die voor een deel kapot zijn door een oorlog”.

In the English translation, it can be observed that additional information has been added, accompanied by a parenthesis. “The ruins of borg Ewsum (a fortified countryhouse), partially destroyed by war, are visible in the background”. Given the painting is inherently Dutch, centrally depicting an estate in the Netherlands within the background, the translator decided to keep the official Dutch name of the estate, opting for writing additional information in the form of a short description. The Dutch cultural element remains, providing nonDutch speakers with an opportunity to become familiar with the unknown word.

Adding an English equivalent serves as an educating tool for international visitors,

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while also respecting the Dutch heritage.

The second example is the label for Barthold Entens van Mentheda from 1572. The artwork portrays the man in a contrapposto position with his gaze upwards. The coat of arms and objects associated with warfare are clearly visible in the background, and the importance of the figure is further accentuated by the use of warm hues, as well as saturated colours of clothing. There is also a clear inscription at the lower left corner. In the case of these labels, rather than describing Dutch architecture seen in a landscape, the specific terminology is being explained.

The Dutch label reads as follows: “Hij is vooral bekend als watergeus,” while the English label is much more detailed in the description: “He is most famous for being a watergeus (a Dutch sea-roaming rebel who opposed Spanish rule).” With this explanation, non-Dutch speakers are again invited to learn a new term in this Dutch context, following the idea that the exhibition revolves around the history and culture of Groningen.

This proves how a literal translation is not always a superior option, as the nuance might be lost.

What is more, visitors are able to write their thoughts around the label, both in English and Dutch. The table accommodates space for both Dutch and English labels, allowing connection to all museum visitors.

It can be also observed that both English and Dutch comments appear across the whole table, not only in relation with the language-matched labels, illustrating the connection between national and international guests. The curators ensure all voices are being heard.

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CONCLUSION In conclusion, the visual and linguistic aspects of the labels at the exhibition were considered in order to demonstrate how the Museum aan de A with their exposition Who writes History? at the Groninger Museum includes both Dutch and nonDutch visitors, inviting them to express their ideas and opinions, as well as raise significant questions.

The exhibition offers inclusion through English translations, which also contain additional information in case the cultural or historical background of the Netherlands might be unknown to international visitors.

The distinction between facts and thoughts makes it easier for non-Dutch speakers to follow the text, and the translated labels enable international visitors’ expression through writing.

It can be understood that a degree of exclusion is still present, due to the fact that English texts are much smaller than the Dutch ones. However, it should be remembered that the texts cannot be identical. The distinction between them helps the visitor identify the label they would like to read easily. Furthermore, there is not enough space for both English and Dutch labels to be of the same size.

This would give rise to different issues, such as how exactly does one distinguish the labels if they are designed in the same manner? It could be more confusing to both Dutch and non-Dutch speaking audiences, as they would merge visually.

Finally, the exhibition is displayed in a Dutch-based museum. The exhibition’s primary audience is the Dutch community, as a demographic which is relevant due to the theme of the Museum aan de A, which is dedicated to Groningen history and culture. The exhibition, therefore, serves as a great example of inclusion through translation, while remaining true to the Dutch aspect, both in linguistic and cultural dimensions.

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The

ATA

27

Speaking another

SELF

Personality shifts across languages

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“I wish you understood my language, you would see how funny I really am” a thought that comes up regularly in multilingual friendships at international universities. Speaking a non-native language can often feel like operating within hidden boundaries, where humor is harder to convey, jokes land differently and even decisions or emotions feel distorted. But did you ever consider what these everyday experiences really show us? What is it about language that can change the way we feel, think and even express who we are, sometimes leaving parts of our personality “lost in translation”?

As someone who has struggled with decision-making for as long as I can remember, I was surprised to learn that language can be one of the variables influencing rationality of our decisions. It has been found that when people operate in a non-native language, emotional reactions tend to feel less intense and we start thinking more analytically (Keysar et al., 2012; Costa et al., 2014). Similarly, scholars studying linguistic relativity argue that different languages carry their own framework of organizing meaning, which shapes how we perceive and interpret the world (Slobin, 2003; Boroditsky, 2011). Such findings highlight that switching languages does not only change vocabulary but can also activate different cognitive, emotional and social processes within our brain. So, what happens in the gaps between languages, where meaning is not simply transferred but transformed?

As mentioned earlier, one of the most significant mechanisms involved in language switching concerns emotional resonance, or the extent to which information presented feels emotionally meaningful, which often becomes weaker in a second language (Weimer et al., 2022). A well-documented manifestation of this is the foreign language effect, which leads to reduction in common emotional biases in decision-making processes in a non-native language, as demonstrated by Keysar et al. (2012). In their study, participants were presented with risky-choice dilemmas with potential gains and losses in a native or foreign language and the results showed that cognitive bias like loss aversion were less common in the foreign language group. This is a good illustration of how operating in a second language can create psychological distance, making emotionally charged decisions feel less overwhelming in a non-native tongue. Likewise, emotionally charged words in a foreign language happen to carry less visceral weight than ones expressed in one’s first language (Pavlenko, 2008). Expressing affection, swearing or describing vivid memories may feel dampened, showcased by reduced physiological reactions associated with emotional arousal such as skin conductance (Harris et al., 2003, Pavlenko, 2008).

Part of this phenomenon is grounded in cognitive load, meaning that processing a second language requires additional mental effort devoted to considering grammar, vocabulary and syntax of a second language, which can reduce spontaneity and make it harder to convey nuanced meanings such as humor, affection or intense emotions (Hasegawa et al., 2002; Tang et al., 2025). At a deeper structural level, theories of linguistic relativity suggest that the way in which concepts like agency, temporality and manner of action get grammatically encoded affects how humans habitually perceive and conceptualize events (Slobin, 1996; Slobin, 2004; Lucy, 1996).

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Building on how language shapes habitual perception and conceptualization of life experiences, I would like to explore how this effect applies to development of the social identity and self-concept based on long-term experiences in specific linguistic contexts. As someone who completely moved places of residence twice in my life, in childhood with my family and later for university, I often notice that my default mindset, including the ways how I naturally feel, think and interact, shifts depending on the linguistic context I am in. This is something that many international students can resonate with, but why exactly does it sometimes feel like we are translating not only words but also parts of who we are?

A common explanation is that long-term experiences in particular linguistic environments shape differing versions of self by encoding and retrieving autobiographical memories in language-dependent ways. Research on bilingual memory demonstrates that recall is more accessible and detailed when participants are asked to retrieve an experience in the same language in which it was encoded (Marian & Neisser, 2000; Schrauf &Rubin, 2001). Pavlenko (2006) further argues that different languages produce distinct autobiographical narratives since each language is linked to specific socialization and schooling contexts, relationships, media exposure, through which we get to know ourselves as we develop interests, values and opinions. As a result, we start associating languages with different social self-images, identity positions, narrative traditions and even affective backgrounds, reinforcing particular ways of interpreting social situations and expressing the self across various linguistic contexts.

These differences in identity also get reinforced through daily social interaction.

Communication Accommodation Theory as well as research on linguistic style matching suggest that speakers unconsciously adjust their speech patterns, lexical choices, tone and expressions to match their linguistic community, giving rise to a phenomenon often called “shadowing” (Giles & Ogay, 2013; Ireland & Pennebaker, 2010). This shadowing process extends to culturally embedded media content like books, films or online content, which all also provide models of behavior, emotional expression, humor and social norms. According to cultivation theory, long-term exposure to such media types in a selected language forms viewers’ understanding of social reality associated with it, which we internalize and use as a reference for self-presentation (Gerbner et al., 2002). Together, these mechanisms help explain how situating yourself in a new language frame constructs a new layer of identity with novel memory networks and social schemas, leaving part of our previous self partially untranslatable.

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Nevertheless, beyond the many mechanisms operating at an unconscious cognitive level, we as humans possess a fundamental desire to fit in and be perceived favorably by others. This motivation builds the ground for the concept of cultural frame switching, which explains that cultural cues, including language, activate a specific interpretive lens through which people perceive, analyze and respond in social situations (Hong et al., 2000). For example, participants from a group of Spanish-English bilinguals reported being more extraverted, agreeable and conscientious in English than in Spanish, showcasing how cultural frame switching prompts individuals to adjust their self-expression to culturally valued norms like assertiveness and achievement in English-speaking individualistic contexts (Ramirez Esparza et al., 2006). In this case, language does not only trigger different ways of self discovery or communication, but it also invites active identity negotiation as individuals can emphasize traits important in a given context while temporarily downplaying others. Thus, sometimes what appears as parts of personality being lost can represent an active adaptation process, where fitting in requires subtly reshaping the self.

Altogether, these insights suggest that what we sometimes experience as our sense of self getting lost in translation is not just words failing to capture meaning, but a deeper mechanism of language shaping cognition, emotion, memory and identity. This has the power to activate multiple layers of one’s inner world that can operate differently across linguistic and cultural contexts, uncovering traits, perspectives and ways of being that would otherwise stay hidden, perfectly reflecting the famous Czech proverb

References

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31

When God Became Intelligible

How Translation Caused the Loss of Divine Ambiguity From Word to Logos to Machine Learning – the Rewriting of Religious Authority

By Sofia Lull

Introduction Translation is commonly understood as a technical exercise: a means of conveying meaning from one language to another with minimal distortion. (1) In religious contexts, this assumption carries particular weight, as translation is often regarded as a necessary yet subordinate tool for preserving divine revelation – the belief that God communicates with humanity through sacred texts across time and place. (2) Yet this view obscures a deeper problem. When sacred texts are translated, what is at stake is not only semantic fidelity, but the conditions under which the divine is understood. Translation does not simply communicate revelation; it structures the conceptual space in which it can appear.

This essay argues that translation can be ontological: it imposes equivalence between fundamentally different linguistic worlds, shaping both how God is understood and who is authorized to interpret divine meaning. (3) Because religious belief depends on what is accepted as a valid interpretation of revelation, translation quietly stabilizes certain understandings while excluding others. Using the Septuagint as a case study, this piece shows how translation rendered revelation intelligible within the Greek philosophical framework. It proceeds in three steps: first, by reconstructing revelation as event and ambiguity in the Hebrew Bible before translation; second, by showing how translation transformed this structure by imposing conceptual stabilization; and third, by analyzing how this shift reconfigured authority through logos. Throughout the analysis, it suggests that this dynamic reappears in contemporary machine-learning systems, which similarly define the conditions under which meaning can be recognized.

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Revelation Before Translation: Event, Relation, and Ambiguity

Before turning to the philosophical consequences of translation, it is necessary to clarify what “revelation” – the idea that the divine discloses itself to humans through an act of communication that originates beyond human logic – means in its pre-translation context. In the Hebrew Bible, divine speech is fundamentally ‘performative’ rather than descriptive: it does not simply represent reality but enacts obligations and brings about observable change. (4) Meaning arises through interactions since this mode of communication is situational and relational.

God speaks through commands, promises, and interruptions — moments that disrupt ordinary expectations and call for a response — rather than offering abstract explanations of moral duty.

(5) Revelation, in this sense, unfolds within time and context. It is embedded in narrative rather than organized into a systematic doctrine.

Hebrew religious language, in fact, permits semantic openness, with meaning shaped by unfolding circumstances, never fixed in advance. (6) Religious authority is sustained through this system, which preserves the asymmetry between divine address and human understanding. Divine utterances do not function as general propositions but as interventions whose significance depends on who is addressed, when, and under what conditions.

The divine self-identification in Exodus 3:14 (“I will be who I will be”) exemplifies this logic. The divine resists definitional closure and situates His identity in future action rather than in a metaphysical essence. Likewise, covenantal declarations such as “I will be your God, and you shall be my people” derive meaning through historical unfolding — through ongoing practice and obedience, moments of rupture such as exile or disobedience, and acts of renewal that reinterpret earlier utterances. In many cases, the meaning of revelation becomes clear only retrospectively. (7) Its authority lies precisely in its resistance to full conceptual capture, exceeding any single, human-made fixed formulation. This dynamic is equally evident in divine commands.

In the Hebrew Bible, expressions such as “you shall” or “you shall not” derive their authority from performative force rather than from an underlying theory of law. Law is enacted as a divine command before it is abstracted into a principle, and divine speech carries authority not because it is immediately coherent, but because it interrupts established expectations and demands a response. (8)

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These examples show that, in the Hebrew Bible, revelation operated as an event that claimed authority through encounter, which demonstrates that divine speech was “performative” in the sense that it did something specific: it issued commands, established relationships, and brought about change, rather than merely described a state of affairs. Because such speech is always addressed to particular people in specific situations, it resists abstraction into universal definitions. Its authority, therefore, does not depend on clarity at the moment of utterance, but on its capacity to address, unsettle, and obligate its audience. This helps clarify what is meant by “interruption.” Divine speech often disrupts the expectations of its human recipients — their assumptions about justice, order, or their own role within a given situation. It calls them to act in ways that may not be fully intelligible in advance, thereby reorienting their understanding through their responses. In this sense, ambiguity is not a weakness but a condition of authority: it preserves the gap between divine address and human comprehension.

What is at stake in this structure, which is the preservation of ambiguity as a condition of authority, anticipates contemporary concerns about systems that promise understanding by eliminating interpretive openness.

When ambiguity is treated as inefficiency, authority shifts away from situated encounters and toward a stable, systematized explanation of the text’s meaning, which assumes that divine interpretation is fixed, transparent, and context–independent.

Translation as Philosophical Constraint: From Event to Concept Translation destabilized the Hebrew Bible’s form of revelation. When revelation is rendered into another language — especially one governed by different epistemic assumptions and philosophical frameworks — ambiguity becomes a problem to be resolved rather than a space to be inhabited. Similar to contemporary machine learning systems, which are designed to produce stable and repeatable outputs, translation exerts pressure toward resolution and coherence: multiple meanings are narrowed, context-specific expressions are generalized, and narrative tensions are stabilized. In religious contexts, this pressure is inseparable from authority, since whoever resolves ambiguity determines what divine authority means and how it may be interpreted. (9)

Historical Context: The Septuagint The Septuagint is the ancient Greek translation of the Hebrew Bible (the Tanakh), produced between the 3rd and 2nd centuries BCE, most likely in Alexandria. It emerged in a multilingual environment where Greek was the dominant language, alongside Egyptian and Persian cultural influences. The translation was undertaken for Jewish communities whose primary language had become Greek, and it represents one of the earliest and most influential instances of large-scale religious translation, shaping later Christian and Jewish traditions.

The Septuagint was produced in a Hellenistic intellectual environment in which Greek philosophy shaped prevailing conceptions of logic, reason, and order. Greek was therefore not a neutral medium for Hebrew thought, but a language structured by the expectation that truth be coherent, stable, and conceptually expressible. (10) Within this framework, translation did not simply transmit meaning but reorganized it, introducing pressure to resolve ambiguity at the level of grammar and vocabulary. This produced a shift from action to essence.

Dynamic, event-based descriptions of divine activity in Hebrew were rendered into more static, predicative forms in Greek, so that what God does becomes what God is.

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In this way, narrative expressions of divine intervention are recast as attributes of a consistent, intelligible identity. What appears as clarification is better understood as reclassification: temporally unfolding actions were translated into conceptually stable categories, reflecting a deeper commitment embedded in Greek thought. Unlike Hebrew semantic openness, Greek metaphysics prioritizes His stable being over His unfolding action and coherence over situational occurrence. (8) Translation therefore operates as a selective constraint, aligning divine meaning with an ontology in which what truly exists must be conceptually graspable. Within such a framework, elements of the Hebrew text that resisted systematization, such as shifts in tone and moments where meaning depended on narrative context, were no longer preserved. Instead, they were absorbed into generalized, abstract formulations that smoothed over discontinuity. What was lost in this process was not simply linguistic nuance, but the capacity of the text to sustain meanings that emerged only through narrative development and human interruption.

This pressure becomes most apparent at the level of lexical choice. When a Hebrew term carries multiple interpretive possibilities, the Greek translation must select a single equivalent.

For instance, nephesh — which can denote “life,” “breath,” “living being,” or “self” — is rendered as psychē, reflecting a more bounded, philosophical notion of the soul while excluding its more relational and embodied senses. (9) In such cases, interpretive authority shifts away from the unfolding narrative context, where meaning remains open, toward a framework that prioritizes definitional clarity. Crucially, this shift does not result from isolated mistranslations. It emerges cumulatively, through repeated acts of equivalence that consistently favor conceptual unity over semantic plurality. Over time, translation stabilized divine meaning within the limits of what could be systematized, making intelligibility the standard by which revelation could be understood. One of the most consequential outcomes of this process was the transformation of divine speech into divine reason. Where the Hebrew text foregrounds God as one who speaks and acts (dābār, okhmāh), the Greek translation renders God in terms of principle and order (logos, sophía). (10) Revelation thus became something to be grasped conceptually rather than encountered contingently.

A structurally similar dynamic can be observed in large language models, which process terminologies by transforming context-dependent expressions into discrete representations, selecting one interpretation while excluding others. Multiple potential meanings are compressed into a single, high-probability output, producing consistency at the cost of semantic range. What appears as clarification is, in both cases, a stabilization of meaning within predefined limits, with authority accrued to those who define and operationalize them.

Logos and the Reconfiguration of Authority The shift from performative, context-bound revelation to conceptually stabilized meaning becomes most visible in the adoption of logos as a framework for understanding divine speech. In Greek philosophical usage, logos does not simply mean “word,” but refers to a principle of rational order that structures thought, language, and reality. (11) It assumes that what is spoken can be rendered intelligible — grasped, organized, and integrated into a coherent system. This marks a decisive departure from the Hebrew understanding of speech as an event that unfolds within specific situations. When divine communication is interpreted through this conceptual lens, it is no longer primarily something that occurs, but something that can be explained. (12) The narrative-based God who speaks, commands, and interrupts becomes an object of reflection within a pre-defined system of meaning. Revelation is thereby recast: not as an encounter that demands response, but as content that can be formulated, analyzed, and taught. Once rendered in this form, it becomes portable across contexts. It can be codified into doctrines, transmitted through instruction, and stabilized through interpretive frameworks that depend on consistency rather than relational engagement. In this sense, logos does more than translate divine speech; it makes it administrable, and thus capable to be regulated, defended, and institutionalized. (13)

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Although this transformation facilitates clearer communication, it carries direct implications for authority.

When revelation is treated as intelligible content, authority shifts toward those who can interpret and systematize it.

Intelligibility becomes a criterion of legitimacy: meanings that cannot be rendered coherent within the dominant framework are likely to be dismissed as obscure, contradictory, or irrelevant. In this way, semantic openness does not merely resist understanding; it risks exclusion from what counts as valid knowledge. The question of revelation (“what has been said?”) becomes inseparable from the question of expertise (“who can explain it?”).

Interpretative authority no longer resides primarily in the immediacy of divine address, but in the practices that reproduce identical meaning over time. This can be understood as a transition from responsiveness to expertise, and from encounter to explanation. Translation thus becomes the point at which revelation enters the domain of governance through the demand for coherence as a condition of meaning itself.

A parallel dynamic appears in deep neural networks within artificial intelligence.

Recognition of “truth” depends on legibility: inputs must conform to representational structures in order to be processed. What cannot be formalized is not simply misunderstood but rendered inoperative. (14) Authority, in turn, accrues to outputs that align with the system’s internal criteria of coherence and probability. As in the case of logos, intelligibility governs not only meaning but its conditions of appearance. The increasing use of these systems to engage with religious texts further extends such dangerous dynamics. When systems are used to ask questions of scripture, they reproduce privilege-dominant, high-probability interpretations. As a result, AI-mediated engagement with religious texts risks shifting from a critical and interpretive practice to one that reproduces standardized meaning.

(15) This is particularly significant in religious traditions where interpretive plurality is not incidental but constitutive of textual authority. In such contexts — such as Catholicism, with its deep reliance on metaphor and layered interpretation — meaning emerges through sustained engagement rather than fixed definition. When ambiguity is filtered out in favor of consensus, religious “accuracy” becomes aligned with statistical regularity rather than sustained interpretive engagement, thereby narrowing the conditions under which meaning — and, by extension, the divine — can be encountered.

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Conclusion This essay has argued that the translation of religious texts reshapes the conditions under which the divine can be understood. Using the Septuagint as a case study, it has shown that rendering Hebrew revelation into Greek reoriented meaning toward intelligibility, coherence, and conceptual stability, priorities that do not necessarily reflect the intentions of the original text. In resolving linguistic ambiguity through philosophical equivalence, translation transformed divine encounter into a precise conceptual form, shifting revelation from event to structure. What was diminished in this process was the openness through which meaning exceeds fixed interpretation. Ambiguity, in most religious contexts, is not a deficiency but a condition of transcendence. Its reduction narrows the space in which the divine can appear, and what emerges is a model in which understanding depends less on response to an encounter and more on the capacity to systematize and explain.

This dynamic extends beyond the historical case of the Septuagint. All systems that privilege clarity and coherence inevitably determine which meanings remain viable. Translation between conceptual frameworks is therefore not simply a transfer of content, but a mechanism that establishes the limits of intelligibility.

Seen in this light, contemporary machine-learning systems reproduce a comparable structure. Just as Greek translation aligned Hebrew revelation with philosophical standards of coherence and order, artificial intelligence systems organize meaning according to pre-defined criteria such as consistency, predictability, and usability. In both cases, authority is relocated and embedded in the logic of the mediating system. What persists is what can be rendered stable and legible within that system, while forms of meaning that depend on ambiguity, interruption, or context recede from view.

The question, then, is not whether translation can be avoided, but what kind of meaning it permits to endure.

When intelligibility becomes the primary condition of legitimacy, the result is not the elimination of transcendence, but its displacement. Translation does not simply carry meaning across boundaries; it defines the terms under which meaning remains possible.

References 1 Nida, E. A., & Taber, C. R. (2003). The theory and practice of translation. https://archive.org/details/theorypracticeof0000unse_p0n2 2 McGrath, A. E. (2011). Christian theology: An introduction (5th ed.). Wiley-Blackwell. https://www.cur.ac.rw/mis/main/library/documents/book_file/digital-65aa711508f4e3.4850060 7.pdf 3 Steiner, G. (1998). After Babel: Aspects of language and translation (3rd ed.). Oxford University Press. https://global.oup.com/academic/product/after-babel-9780192880932 4 Austin, J. L. (1975). How to do things with words (2nd ed.). Harvard University Press. https://www.hup.harvard.edu/books/9780674411524 5 Brueggemann, W. (1997). Theology of the Old Testament. Fortress Press. https://archive.org/details/theologyofoldtes0000brue 6 Barr, J. (1961). The semantics of biblical language. Oxford University Press. https://archive.org/details/semanticsofbibli0000barr 7 Ricoeur, P. (1981). Hermeneutics and the human sciences. Cambridge University Press. https://archive.org/details/hermeneuticshuma0000ricu 8 Buber, M. (1962). The prophetic faith. Harper & Row. https://archive.org/details/propheticfaith00bube 9 Venuti, L. (2012). The translator’s invisibility: A history of translation (2nd ed.). Routledge.

11 https://cbpbu.ac.in/userfiles/file/2020/STUDY_MAT/ENGLISH/JS/venuti.pdf 10 Hengel, M. (2002). The Septuagint as Christian scripture. T&T Clark. http://khazarzar.skeptik.net/books/hengel01.pdf 11 Kahn, C. H. (1979). The art and thought of Heraclitus. Cambridge University Press. https://www.cambridge.org/core/books/art-and-thought-of-heraclitus/7502B5597B549A22A3BE2D218F F542F4 12 Gadamer, H.-G. (2004). Truth and method (2nd rev. ed.). Continuum. https://web.mit.edu/kaclark/www/gadamer_truth_and_method.pdf 13 Foucault, M. (1980). Power/knowledge. Pantheon Books. https://monoskop.org/images/5/5d/Foucault_Michel_Power_Knowledge_Selected_Interviews_and_Other _Writings_1972-1977.pdf 14 Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press. https://www.deeplearningbook.org/ 15 Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT ‘21. https://dl.acm.org/doi/10.1145/3442188.3445922

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Languages of

POWER

The Hegemony of English in the Global Language System

By Justine Laus

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English is not the language of English speakers.

It belongs to me too if I want to keep up my relations with the wider world.“ Anonymous Administrator French Business School, 2004 [1]

In 2024, Times Higher education declared the Rijksuniversiteit Groningen to be within the top 30 most international Universities worldwide.

The ranking bases itself not only on the international student score, but also on the international staff and co-authorship score as well as reputation metrics, determining which institutions provide truly international environments for prospective students [2]. This internationality often relies on an important vehicle to enable communication across varying cultural groups: the use of the English language in research, teaching and learning.

Like many international students studying at the RUG, my relationship to language can be quite complicated. For many, English is a second, third or fourth language that defines much of social and academic life in the Netherlands. In friend groups shaped by different origins and mother tongues, it is the language building bridges, uniting everyone in one conversation and creating fluid discourse without major misunderstandings. Not only is this relevant on a social level, but the opportunities of studying an English taught degree are evident to many, especially when looking at prospects in academic and professional settings. Though its role has become so central in our lives, we rarely question the provenance and the dynamics of this linguistic hegemony that is present on a global level.

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History & Hierarchy I remember that when I was younger and starting to learn English, it was immediately introduced to me as the “world language”. Naturally, I assumed that this had been decided by a formal international agreement of some sort, based on its practicality and relatively easy grammar.

It was only much later I understood the relevance of international norms, and how informal societal standards can constitute strong rules in themselves, without the need for signatures and handshakes. Upheld by societal expectations, its importance only persists through the mutual compliance of international actors and private persons like you and I. The reference to English as a seemingly neutral instrument for international communication between people not sharing the same native language is often resumed to the label of Lingua Franca [3].

Despite its majoritarily informal nature, the ascent of English to become a Lingua Franca can be tracked in a very tangible way through the documentation of official languages of international institutions and agencies over time.

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On a global level, what can initially be observed is a gradual shift from Latin, predominantly used for international affairs until the middle of the 17th century, to French. The former was notably used in the Westphalian Peace Treaties, only being translated to German a few weeks later due to a private initiative. Surprisingly, this shift to French persisted despite the defeat of Napoleon and was used to produce the Act of the Congress of Vienna in 1815 as well as other important historic legal and philosophical texts [4].

This was not coincidental, as France enjoyed a particular political, economic, but also cultural, technological and ideological dominance in Europe at the time [1].

In the 17th century, the monarchy’s conscious centering of culture and their patronage of the arts to bolster prestige led to a spread of French culture and the French language in courts across Europe.

Furthermore new ideas concerning the state, and democratic government arose through the writings of Montesquieu, Voltaire and Rousseau, which were only accessible to those statesmen that had acquired the knowledge of French.

English only started gaining significant importance in international affairs in the 18th century. As an example, during the Peace Conference in Paris in 1919, while France demanded the negotiations should be held in French, it eventually had to accept the equivalence of the English language due to contestation from the US and the UK [4]. Both the English as well as the French Version of the Treaty are deemed authentic as per Article 440(3) of the Treaty of Versailles [5].

These developments were of course not isolated from the current prevailing distributions of political, economical and cultural power. As can be observed, the emergence of the US as a global superpower after World War II cemented the presence of the English language in international affairs [6] . France, in contrast, was diminished by its defeat and was not represented in the Yalta and Potsdam discussions, thus French not being of need in mediation [1].

While these tensions persisted and French as a Lingua Franca was waning, the creation of the UN established a new, multilingual system, in an attempt to diversify the use of language and encourage a shift away from that of the colonial powers. Thus, today the organisation operates a multilingual system based on 6 languages. This decision shows that the founders of the UN were well-aware of the role the choice of language of discussion and mediation in international affairs plays for their respective reach and hence implied power [4].

Generally, the value we collectively assign to the English language as a communicative tool today stems from its communicative reach and the doors it can open to us. This power, which is unevenly distributed across the globe, has been theorised by Abram de Swaan in his theory of the dynamics of the Global Language System [7]. He presents the global language landscape as a pyramid with four different levels. English occupies a unique role as it is the only language in its category as a hyper-central language that has an almost universal global reach.

Languages like French and Spanish have a wide reach but are attributed to the group of a dozen super-central languages. Central Languages in turn are mostly languages officially used by nation-states, and “peripheral languages” are the overwhelming majority as they account for an estimated 98% of the world's languages [7].

This pyramidical structure effectively demonstrates the power structure that the choice and knowledge of language holds, as speakers of a lower language group need to learn a more central language to communicate outside of their community, reaching the next level: the international sphere, and by learning English, reach a truly global means of communication [8]. In contrast, native speakers of super central and hyper central languages have the privilege to not necessarily see a need to acquire knowledge of a peripheral language.

This reality applies to the day to day lives of students at the RUG, as many international students learn English as a hypercentral language, while not learning Dutch, due to its lower standing on the pyramid and diminished reach from native languages. The hierarchy embedded in the choice of language becomes crystal clear when realising that the norm not only dictates the most advantageous choice of language, but its very use in international or national affairs can reinforce or weaken its reach and therefore relative value on the pyramid. The norm is then continuously reinforcing itself as compliance is rewarded with ever growing benefits.

The choice of what language to use as a standard is then deeply political and clearly reflects constellations of pre-existing power [4].

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Multilingualism, Accentism, Privilege Someone speaking with a U.S. American accent will likely be looked at differently in discourse than someone with a strong Scottish accent. Ethnic heritage and social class are thoroughly intertwined with accent discrimination and the prejudices certain accents have to face [10]. This idea of a “standard English accent” , which differs based on geographical region and state, is a norm that strongly favours English monolingual groups in social situations but also in academia and work environments [10] .

On a more individual level, in the setting of international relations and academia, native speakers of official languages and especially English enjoy a far greater power of persuasion than their peers who learned the languages later in life. Especially in oral presentations, the individual speaking with a clear, fluid and natural English will regularly be seen as more competent than their peers who might never truly surpass a practiced air and rigid sentences [4]. This is not only a sign of the power the English language exerts in academic and professional exchange, but also one of ignorance [9].

Without the need to learn another language that is lower on the pyramid, many English speakers remain monolingual speakers and will likely never be faced with conducting business talks, learning, and official interactions in a language other than their own. Even learning another language, this new skill will likely never come to be used in crucial situations where clear communication and transmission of important information is key. It is much easier to take the path of least resistance and handle things in English.

The risk of sounding “strange” or inadequate and the need to adapt oneself to a different mode of communication and culture then relies on the person that is not native to English [9]. This is directly related to the phenomenon of accentism, a form of social bias based on the accent of a person.

The explanation for accentism spreads across social identity theory, cognition and evolutionary psychology [9], but what is evident is that accentism directly reproduces the power dynamics I previously described. Experiences of accentism are intersectionally connected to ethnicity, race, gender, and nationality [10] .

As such, it constitutes an important marker to prove one’s belonging to a state or nation. When looking at English as a “world language” or a connecting language in academia, this dynamic becomes more complicated. As the language is spoken across different countries, accentism applies to native speakers and foreign-accented English speakers [11].

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However this is not to say that this is a problem unique to the English language. While less prevalent in global settings due to the lower standing on the pyramid, super-central languages are also prone to showcase a tendency for accentism among speakers. A good example would be French, which used to be a lingua Franca and also comprises a wide variety of nations and regions as part of the francophone world.

However it is important to note that the key sociolinguistic difference between the languages is that French is regularly considered a monocentric language, with Paris representing the unique center of the francophone world surrounded by more peripheral regions of use, while English is considered a pluricentric language with different points of reference [12]. While this centrality persists, recent studies also showcase that there seems to be an emergence of new centers of French, creating new reference points, such as in the Suisse Romande and Quebec.

Interestingly enough, while multilingualism is treated as a particular linguistic condition which garners much research interest in the field, multilinguals represent a majority in contrast to Monolingual speakers in the world [8]. In fact, the specific monolingual perspective on language is relatively recent, starting in the 19th and 20th century, making the portrayal of multilingualism as a novel and modern phenomenon quite ironic [8].

The emergence of the monolingual perspective emerged jointly with that of the nation-state and was combined with efforts to unite the territory under one language.

While linguistic diversity has been preserved better n certain states such as Spain and Ireland, when looking at France after the Treaty of Westphalia, integrating the newly annexed regions into a common French system was a key political priority [13]. Today, while 75 languages are recognised as "languages of France” only very few of them are still spoken, and only French is deemed an official national language [14]. This showcases how certain languages in de Swaan’s framework obtained their power not only from dynamics of domination during colonialism for hyper central and super central languages, but also on the level of the state, including central languages. This linguistic domination happening on multiple levels then directly impacted the scientific field of linguistics, restricting it heavily to a generally ahistorical monolingual norm in research and analysis.

Nevertheless the concept of accentism, which in reverse can translate to so-called linguistic insecurity in the accented speaker is still very much present in the francophonie, if not more so due to the centralist sociolinguistic structure of the language. Anyone who has tried to order a coffee and a croissant in Paris with high school French will have been witness to the direct effects of this dynamic.

Despite this, monolingualism has been increasingly challenged inWestern Europe since the late 20th century, which is reflected in the Council of Europe’s Charter for Regional or Minority languages representing a highly developed legal instrument to revitalise minority languages [1] . Whether these efforts will lead to significant shifts in the national and international power structures of languages is a question left open.

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What do we make of these Power structures ?

Ultimately, as scholars compete for influence and reputation, employing all possible means to fulfil their personal ambitions, most academic work especially in the field of international relations will be formulated in English, or at least another super central or central language [4]. While researching and writing this article, I am aware of the irony of the fact that most of the literature on multilingualism and the hegemony of the English language has been written in English. In fact, the abstract term of “Language” is regularly a signifier for “English” in the literature I employ [8].

If these dynamics of power and linguistics are so deeply embedded into academia itself, what can we, as students of the RUG and aspiring academics take from the recognition of these dynamics?

If anything, writing this article has helped me to reflect on the conversations I might hold with my roommates, friends, and professors, and how they might advantage or disadvantage them. While many of us are actively profiting from the hegemony of the English language, it is important to understand this privilege not as a welcome coincidence, but a historical and political norm, deeply rooted in the development of the current world order. While the choice of language in official academic and social institutions is always a trade-off between communicative reach and linguistic equality, it might just be worth it to give space to your native language in conversation, and in the choice of language in your future research and academic work. Instead of blindly complying with the norm, our lived realities as students in an international environment should directly challenge the monolingual English bias in research and work.

References [1] Wright, S. (2006). FRENCH AS A LINGUA FRANCA. Annual Review of Applied Linguistics, 26, 35–60. https://doi.org/10.1017/S0267190506000031 [2] Most international universities in the world 2025. (2025a, March 19). Times Higher Education. https://www.timeshighereducation.com/student/best-universities/most-international-universities-world [3] Phillipson, R. (2008). Lingua franca or lingua frankensteinia? English in European integration and globalisation. World Englishes, 27(2), 250–267. https://doi.org/10.1111/j.1467-971X.2008.00555.x [4] Tomuschat, C. (2017). The (Hegemonic?) Role of the English Language. Nordic Journal of International Law, 86(2), 196–227. https://doi.org/10.1163/15718107 08602003 [5] Treaty of Versailles, June 28, 1919, https://www.foundingdocs.gov.au/resources/transcripts/cth10_doc_1919.pdf [6] Zeng, J., & Yang, J. (2024). English language hegemony: Retrospect and prospect. Humanities and Social Sciences Communications, 11(1), 317. https://doi.org/10.1057/s41599-024-02821-z [7] De Swaan, A. (2013). Words of the World : the Global Language System. Wiley. https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=1209427 [8] Piller, I. (2016). Monolingual ways of seeing multilingualism. Journal of Multicultural Discourses, 11(1), 25–33. https://doi.org/10.1080/17447143.2015.1102921 [9] Hegarty, P. (2020). Strangers and States: Situating Accentism in a World of Nations. Journal of Language and Social Psychology, 39(1), 172–179.https://doi.org/10.1177/0261927X19884093 [10] Dryden, S., & Dovchin, S. (2024). Accentism: English LX users of migrant background in Australia. Journal of Multilingual and Multicultural Development, 45(5), 1466–1478. https://doi.org/10.1080/01434632.2021.1980573 [11] Orelus, P. W. (2020). Other People’s English Accents Matter: Challenging Standard English Accent Hegemony. Excellence in Education Journal, 9(1), 120 148.

[12] Chalier, M. (2021). Les normes de prononciation du français: Uneétude perceptive panfrancophone. Walter de Gruyter GmbH & CoKG [13] Van Goethem, H. (1989). La politique des langues en France, 1620-1804. https://doi.org/10.3406/rnord.1989.4455 [14]. Promouvoir les langues de France | Ministère de la Culture. (n.d.). https://www.culture.gouv.fr/thematiques/langue-francaise-et-langues-de-france/agir-pour-les-langues/promouvoir-les-langues-de-france

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45

By Maia Christensen

MA C H I N E L E A R N I N G A TOOL FOR SEEING THE INVISIBLE How do you determine the difference between two invisible objects? Photons (particles of light) and neutrons (found in the nucleus of atoms) are both neutral particles, i.e. are neither positive or negative. In terms of detection, this makes them essentially ‘ghostlike’ and able to pass through large amounts of matter without interacting. However, once they interact with a special detector, the particles produce slightly different pulses. which then must be classified, and human logic struggles to achieve this at large scales. It then falls to other data analysis techniques, such as Pulse Shape Analysis (PSA)[1], which uses the shape of the pulses arising from the respective particles to distinguish them, however fails at low energies, or alternatively, machine learning (ML) techniques, as will be discussed in this article.

As part of the Deepening aspect of the FSE Honours College, we are required to take part in a research project of our choice. Wanting to work in the realm of nuclear physics (for energy, not bombs), I was immediately drawn to Myroslav Kavatsyuk’s group. Their research focuses on the use of lead (which used to be in paints and toys but has since been banned due to its toxicity) as a coolant for nuclear fission reactors. Nuclear fission is the term used for the reaction in which a heavier nucleus splits into two lighter ones, releasing energy, radiation, and free neutrons in the process. This currently provides 9% of the world's energy [2], and 70% of energy in France, the highest share of any country[3]!

The energy this releases causes the system to heat up intensively, and in order to avoid a nuclear meltdown a coolant is needed. This has typically been water, however recent developments have shown lead to be a viable option. Amongst other projects, Kavatsyuk's group is working on refining the properties of lead, as is required for better design of the reactors. They are doing so by firing neutrons at a lead target surrounded by detectors. The neutrons interact with the lead in varying ways, resulting either in a scattered neutron only (elastic scattering), or the same neutron at a lower energy and a photon (inelastic scattering).

The resulting particles are then detected by the detectors, but the measured signals are difficult to classify.

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The project I am undertaking attempts to use ML techniques to see if it can distinguish the two particles better than conventional PSA techniques, hopefully allowing for a better analysis of the effect of the incoming neutrons on the lead. Currently, valuable data in the lower energy regime, in which neutrons and photons cannot be distinguished by a PSA, is simply being discarded. This is an unnecessary waste of valid data, and causes a need for more experiments to run.

Being able to make use of this lower energy data would help decrease systematic uncertainties for the data, and provide more accurate data on lead as a coolant overall.

Individuals unfamiliar with computer science have probably heard of ML in conjunction with Artificial Intelligence (AI). Where AI is the broader concept of computers simulating human intelligence, ML is a subset of this, focused on learning from data. In her book “Machine Learning for Physics and Astronomy”, Viviana Acquaviva describes machine learning as ‘the process of teaching a machine to make informed, data-driven decisions’[4]. This includes recognizing and characterizing objects based on similarities and differences; in my case, distinguishing neutrons and photons. The goal of any ML task is to build a relationship between input and output, acting as a translation tool between the two. In this case, the hope is that ML acts as a tool for translating the energy over time dataset into a (hopefully) clear grouping of neutrons and photons.

However, there are several potential pitfalls to consider when using ML for data analysis. With the development of groundbreaking data analysis methods such as ML, a growth in trust in these methods has followed. ML is revolutionary, with algorithms able to carry out tasks that would take humans months or even years to do by hand, if possible at all.

Although computers and AI can solve advanced problems way faster than any human, they also lack the valuable common sense and logic that humans bring to the table, often causing them to err dramatically. If used ignorantly this can go unnoticed, leading to a misinterpretation of results and thereby a mistranslation of a dataset to false scientific conclusions.

For example, let’s say you have an unbalanced dataset, with 98 neutrons and 5 photons. If you had a model that simply assigned every particle as a neutron, the model would report an accuracy of 95%! While this is technically true, and a high accuracy, using our logic we can clearly see that this is not a very good model. This is called the accuracy paradox in machine learning.

The first step is therefore a critical, logic-based evaluation of whether or not ML is suitable for a task. Acquaviva postulates that when we understand the physics but don’t have data, we should use statistical model fitting, and when we don’t understand the physics but we have the data, or statistical model fitting is insufficient, we should use machine learning [4].

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In the case of distinguishing neutrons and photons, we have the data, but it is too complicated for simple models to classify, with thousands of interactions in a detector leading a single pulse. At high detected energies, the pulse shapes are very different, and a PSA suffices, however at low energies these blend together, and background photons become more significantly, leading to a PSA being unable to distinguish them. Following Acquaviva’s approach we can determine that ML is a fitting tool for tackling this task of translating data into scientific knowledge.

Next we must decide which type of ML to use for the particle classification; supervised or unsupervised.

Supervised models assume that there is a collection of data points for which the target property (particle type) is known, and consists of learning by example through labelling the data. In unsupervised models, no labelled examples exist, and rather than attempting to predict a specific property from the data available, the focus is on discovering patterns in the data. In the case at hand of determining particle type, supervised machine learning is the clear choice. This is the first example of a need for human interpretation and logic in building a valid ML model. Simply chucking your dataset into a ML model will not suffice; purpose-driven choices must be made to ensure that the model accurately yields the desired result.

Within supervised machine learning, several decisions, based on logic and physical intuitions must be made, before one lets the algorithm work its magic. The first step is dividing one’s data for which the particle type is known into a training set, on which one ‘trains’ one’s model, and a testing set, on which one ‘tests’ the just trained model. From this one can go on to apply one’s model to the values for which one doesn’t know the particle types, with a fairly good notion of how well one’s model should perform. The next step is the algorithm itself. While one can technically code one’s own, there are many good preexisting algorithms one can use, coded by others and available to the public. Many of these have parameters that can be set with the aim of achieving a tradeoff between overfitting, where accuracy may be high on one’s training dataset, but it is not generalizable to one’s testing dataset, and underfitting, which is perhaps less accurate on one’s training dataset, but has a better generalization accuracy. One decides the balance oneself when designing a model. One can also determine what one’s model bases accuracy on, i.e. is it the number of misclassified neutrons? Or the number of correctly classified photons? Or some combination thereof?

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While training an ML model for my purpose will (hopefully) allow me to achieve the abovementioned purpose, it is at the cost of information lost in other ways.

Machines evaluate answers based on input parameters, obtained from us. The evaluation process undergone by the machines is often very complex and non-linear, and therefore not transparent for interpretation by humans. Not understanding how a machine came to the answer they gave us inevitably causes a loss of information along the way.

However, it is because of this complexity that ML allows us to collect all kinds of invisible (to us) underlying correlations in the data, and predict based on that. However it is important to note that while this can seem to be ML exhibiting some kind of intellectual properties and ‘understanding’ the data, it is nothing other than reproducing past trends, without any critical evaluation of the input.

In my case, photons and neutrons are getting separated to distinguish between elastic and inelastic scattering, however the majority of the photons are background from the detector itself or the air, and are therefore discarded. In other contexts, photons hold great scientific value where in this case, they are discarded as background information, thereby potentially losing meaningful data. In choosing the specific purpose of a ML model, it is possible that we are losing knowledge of other important physical processes undergone by the ‘background’ photons picked up by the detector. What counts as signal versus noise is never inherent in the translation process, but purpose driven. Machines do not choose these purposes, we do. Translation often involves some type of exclusion, and the meaning we interpret is context dependent. Removing background sharpens one truth, in this case that of the elastic/inelastic scattering incident, while erasing another, the ‘background’ photons. This potential loss of information extends beyond the particle classification case, into any use of ML and AI.

With the rise in the use of AI, and thereby ML, it is important to maintain a deeper understanding of the fact that machines work differently than humans, and do not have any kind of understanding. While it is easy to acknowledge this intellectually, maintaining a continuously critical approach to all machine-created content presents more of a challenge. That is also why, for example, AI responses to the same problem vary significantly depending on the input prompt. This is seen by many daily with Large Language Models (LLMs), which are a specialized type of ML designed to interpret and generate human language. For example, asking ChatGPT, a popular LLM, ‘Is Groningen the best city for students?’ will yield more Groningen-positive results than ‘What are the best cities for students?’, which will provide a wider overview. LLM’s operate based on past experience, but have no intellect and do not analyse, their answers are purely based on probabilities due to past trends. AI, and under that ML and LLM’s, is only as useful or good as the way in which it is programmed, which is based on the people behind the programming.

I am using my Machine Learning model to separate photons and neutrons, hoping to increase the range of reliable particle classification at lower energies. This would open up possibilities to use the same experimental detector setup for new measurements, which are needed but too challenging at present, and would mean that valuable data does not need to be thrown away, simply due to difficulties in classification. This highlights the use of ML in performing data analysis that human logic and statistical models do not suffice for. However, because ML does not possess understanding, intention, or physical intuition and instead operates purely on statistical patterns, it is crucial to keep in mind that human logic and critical thinking are essential in successfully using AI. ML may help us see what human intuition alone cannot, but only through the collaboration of the algorithm and the developer can ML be successful in producing meaningful knowledge.

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References [1] Pulse Shape. (n.d.). Science Direct. Retrieved February 16, 2026, from https://www-sciencedirect-com.proxy-ub.rug.nl/topics/engineering/pulse-shape [2] World Nuclear Organisation. “Nuclear Power in the World Today - World Nuclear Association.” Home Page - World Nuclear Association, https://world-nuclear.org/information-library/current-and-future-generation/nuclear-power-in-the-worldtoday. Accessed 2 Apr. 2026.

[3] Nuclear Power in France - World Nuclear Association. (n.d.). Home Page - World Nuclear Association.

Retrieved February 27, 2026, from https://world-nuclear.org/information-library/country-profiles/countries-a-f/france [4] Acquaviva, V. (2023). Machine Learning for Physics and Astronomy. Princeton University Press.

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Borrowed Words, Contested Meanings Tran sl ation a s Legal Resi stance in Occ upied Japan and Post-S oviet Europe

By M arta Liduma

Introduc tion February 1946. A handful of Americans, most with limited knowledge of Japan, spend a single week drafting a constitution in English for a defeated nation.1 Fast forward to 1991. Three Baltic states, freshly independent, start weaving European human rights provisions into legal systems still shaped by Soviet thinking. 2 What do these moments have in common? Both needed Western legal ideas to be rendered into languages and cultures built on different foundations. Additionally, both raise an awkward question: when you translate legal concepts, do they stay the same?

Scholars have argued about this for decades. Alan Watson thought legal borrowing was easy, pointing to how Roman law spread across Europe and common law took root in former colonies. 3 Pierre Legrand disagreed. He insisted that legal meaning fails to survive transplantation because it’s overly tangled up with local culture.4 Then Gunther Teubner came along with a third option: borrowed rules work like “irritants.” They provoke reactions, and what emerges is something new, something that surprises everyone involved. 5 This essay takes Teubner’s idea and runs with it, comparing how Japan and the Baltic states dealt with imposed Western law through the choices their translators made.

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Tran sl ation a s Legal Method Lawrence Venuti makes a useful distinction.6 Some translation domesticates, pulling foreign texts toward local norms and sanding off the strangeness. Other translation foreignizes, keeping markers of otherness intact. Venuti ties domestication to imperialism, arguing that smooth translation wipes away the source culture’s distinctiveness. Apply this to law, and you’ve got a lens for seeing how recipient societies handle imported concepts. Do they absorb them into existing frameworks? Or preserve their alien feel?

If you combine Venuti’s framework with Teubner’s irritant concept, a pattern reveals itself.

Transplanted rules land in a new system and cause disruption. The system responds by domesticating them, absorbing foreign content into local frameworks. What comes out the other end is a hybrid: traces of both origin and destination, while on the whole being neither. Legrand had a point. The original meaning transforms in transit. But Watson had a point too. Legal borrowing happens, and it produces working legal orders; The trick is recognizing that what travels gets reshaped along the way. The Japanese and Baltic cases show this playing out across different times and places, and they reveal how recipient cultures can strategically use translation to reshape what’s been imposed on them.

Domestication in Occ upied Japan Inoue’s linguistic deep-dive reveals something remarkable.1 Japan’s constitution is really two documents wearing one title. The American version reflects Anglo-American political thinking.

The Japanese version? The language barrier, Inoue argues, remained intact throughout. And the biggest gap opened around a single word: “the people.”

⼈⺠

The American drafters chose jinmin ( ), a term with revolutionary undertones suggesting citizens who hold ultimate political power. Japanese translators systematically replaced it with kokumin ( ), which has a meaning closer to “national subjects” bound to the state. John Dower noticed what this did: it shifted the constitutional foundation away from popular agency and back toward the state and emperor. 7 This was done quietly. Deliberately. Domestication in action, reshaping American intent from within.

国⺠

Hahm and Kim explored how “We the People” gets built through translation across East Asian constitutions.8 Whether you understand the collective sovereign as autonomous citizens or as members tied to a national whole has real institutional consequences. The jinmin/kokumin swap was more than a word choice. It redefined, silently, who holds power.

A similar process happened with “rights.” The word that stuck, kenri ( ), combines characters meaning “power” and “benefit.” It lacks the moral weight of natural rights talk. Hasegawa dug into nineteenth-century debates and found that alternative translations preserving ethical meaning failed to gain traction. 9 The result?

Semantic drift. “Rights” in Japanese can attach to governments as easily as to individuals. Japanese grammar made things harder still.

Speakers routinely drop subjects when context makes reference clear, which downplays individual agency. And the elaborate pronoun system bakes relational hierarchy right into speech. Constitutional language built around autonomous individuals ran into friction at the grammatical level itself. Today’s revision advocates know all this and use it, painting the constitution as an alien imposition that encodes foreign values.10

権利

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ECHR Tran sl ation in PostS oviet State The Baltic experience runs parallel. Again, we see Teubnerian irritation followed by the domesticating response. Sadurski tracked how the European Court of Human Rights scrutinized national laws after eastward expansion, and he noticed another thing: transplanted Western institutions sometimes backfired. 2,11 Motoc and Ziemele’s volume, with chapters by actual ECtHR judges, documents the obstacles. 12 One chapter tackles “translation of the case law of the ECtHR” head-on, acknowledging that this goes well beyond a dictionary problem.

The similarities with Japan are hard to miss. Central European states imported dignity concepts from German constitutionalism, then had to square them with older honor-based traditions. Article 8’s “private life” demanded new terminology where Baltic and Slavic languages carve up the concept of “law” differently than Western languages do. The Soviet-era mindset, oriented toward collective and state interests, clashed with the ECHR’s individualist bent.

In Tammer v. Estonia (2001), Estonia argued that certain expressions carried cultural weight absent from any English equivalent. The Court agreed. That’s judicial recognition that translation raises real legal problems.

Latvian, with its seven grammatical cases, forces legal terms through morphological changes that can shift meaning in subtle ways. Scholars have called for systematic databases to manage the terminological gaps. 13 Yet the Baltic situation carries a unique tension that Japan’s case lacks. These states joined the ECHR system voluntarily, seeking European integration and a clean break from Soviet legal culture. The translation challenges are born from a paradox: the very act of embracing Western norms required filtering them through linguistic and conceptual structures shaped by the system they were trying to leave behind. Japanese translators worked under explicit occupation; Baltic translators worked under the subtler pressure of accession requirements as well as the desire to “return to Europe.” Both contexts produced domestication, yet the motivations differed. Japan’s translators preserved continuity with pre-war traditions; Baltic translators sought transformation while inadvertently preserving Soviet-era conceptual residue.

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Western Doc trines Turned Again st Western Univer sali sm At the risk of dramatic irony, Baltic states have started using domesticated Western doctrines to counter Western universalist claims. In Savickis and Others v. Latvia (Grand Chamber, 2022), Latvia convinced the Court that treating stateless former Soviet citizens (nepilsoņi) differently could be justified through “constitutional identity.” 14 Valiullina v. Latvia (2023) 15 and Džibuti v. Latvia (2023) 16 extended this logic to approve restrictions on Russian-language education. Critics see this as constitutional identity reasoning twisted to justify collective punishment for association with a former occupier.17 Think about that for a moment. Baltic states are wielding Western legal tools to push back in opposition to what they call lingering colonial influence. Western concepts turned against Western universalism.

The margin of appreciation doctrine creates room for exactly this kind of move. It gives states leeway to implement Convention rights according to local conditions. The Latvian cases show how that room can expand, with the Court deferring to national claims rooted in constitutional identity.

And then there is Britain. The UK helped draft the Convention. Now? Political discourse treats Strasbourg jurisprudence as foreign meddling. The abandoned Bill of Rights Bill (2022-2023) would have gutted the Human Rights Act. Conservative leadership has floated leaving the Convention altogether. 18 The founding drafter experiencing its own creation as an external imposition. That perfectly illustrates Teubner’s point. Transplanted legal categories develop their own trajectories. Once domesticated, they acquire meanings that surprise all.

What Thi s Tell s U s Put the Japanese and Baltic cases side by side, and up pops patterns. Both involve Western legal categories entering settings under unequal power conditions. Both have the recipient culture exercising interpretive agency through translation choices. And both confirm that transplanted legal language goes places its authors fail to anticipate. Japanese officials rewrote American constitutional intent through the jinmin/kokumin swap.

Baltic governments use Strasbourg doctrines to restrict minority protections. British politicians denounce their own Convention as alien interference.

Bring Watson, Legrand, Teubner, and Venuti together, and a coherent picture forms. Legal translation produces hybrids. Exporting and importing societies each hold partial interpretive authority, with full control eluding both. Transplanted rules land as irritants, provoking domesticating responses that absorb foreign content into local frameworks while transforming both sides. The hybrids that emerge carry traces of where they came from and where they landed, belonging fully to neither. Time matters also. Japan’s constitution has built up legitimacy through eight decades of use. Yet the revision debates demonstrate that legitimacy stays vulnerable because the translation record exists and can be weaponized politically.

So what’s the takeaway? Legal translation works through ongoing contestation. Power, culture, and meaning keep negotiating juridical authority across linguistic lines. Recipient societies use translation strategically to reshape, resist, and redirect what’s been imposed on them. Sometimes they even turn Western legal categories against Western legal hegemony, which complicates the story about how law travels. What’s needed is a more nuanced view of law as culturally embedded yet capable of real transformation when it crosses borders.

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References 1. Inoue, K. (1991). MacArthur’s Japanese constitution: A linguistic and cultural study of its making.

University of Chicago Press.

2. Sadurski, W. (2012). Constitutionalism and the enlargement of Europe. Oxford University Press.

3. Watson, A. (1993). Legal transplants: An approach to comparative law (2nd ed.). University of Georgia Press.

4. Legrand, P. (1997). The impossibility of ‘legal transplants’. Maastricht Journal of European and Comparative Law, 4(2), 111–124.

5. Teubner, G. (1998). Legal irritants: Good faith in British law or how unifying law ends up in new divergences. Modern Law Review, 61(1), 11–32.

6. Venuti, L. (2008). The translator’s invisibility: A history of translation (2nd ed.). Routledge.

7. Dower, J. (1999). Embracing defeat: Japan in the wake of World War II. W.W. Norton.

8. Hahm, C., & Kim, S. H. (2015). Making we the people: Democratic constitutional founding in postwar Japan and South Korea. Cambridge University Press.

9.

Hasegawa, K. (2009).

Between rights and https://lex.juris.hokudai.ac.jp/~hasegawa/Rights&Kenri.pdf

‘kenri’.

Hokkaido

University.

10. Council on Foreign Relations. (2025). The politics of revising Japan’s constitution. https://www.cfr.org/japan-constitution/politics-of-revision 11. Sadurski, W. (2014). Rights before courts: A study of constitutional courts in postcommunist states of Central and Eastern Europe (2nd ed.). Springer.

12. Motoc, I., & Ziemele, I. (Eds.). (2016). The impact of the ECHR on democratic change in Central and Eastern Europe: Judicial perspectives. Cambridge University Press.

13. Karpinska, L., & Liepiņa, D. (2022). Latvian-English-Latvian electronic lexicographic resources of legal terminology. Baltic Journal of English Language, Literature and Culture, 12, 48–65. https://doi.org/10.22364/BJELLC.12.2022.04 14. Savickis and Others v. Latvia, App. Nos. 49270/11 et al. (European Court of Human Rights [Grand Chamber], June 9, 2022).

15. Valiullina and Others v. Latvia, App. Nos. 56928/19 et al. (European Court of Human Rights, September 14, 2023).

16. Džibuti and Others v. Latvia, App. Nos. 225/20 et al. (European Court of Human Rights, November 16, 2023).

17. Ganty, S., Kochenov, D., & Nugraha, I. Y. (2023, December 21). Constitutional identity vs. human rights: The ECtHR’s bizarre turn in three Latvian cases.

Verfassungsblog. https://verfassungsblog.de/constitutional-identity-vs-human-rights/ 18. Hartmann, J., Carvalho, E., & White, S. (2025, October 9). Do British people want to leave the ECHR? What a decade of polls reveals. The Conversation. https://theconversation.com/do-britishpeople-want-to-leave-the-echr-what-a-decade-of-polls-rev eals-266682

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Colophon Author Names Machine Learning: Maia Christensen What is a Clock?: Janine Brouwer Labels and Their Translations: Zofia Swarzyńska Speaking of Another Self: Vladyslava Besaga Lost in Our Age: Hidde Nijenhuis When God Became Intelligible: Sofia Lull From Sarcasm to Illegality: Laura Mairal Sampedro Borrowed Words, Contested Meanings: Marta Liduma Languages of Power: Justine Laus

Board Members Editor-in-Chief: Evelyn Heidrich Organizational Officer: Alice Rampinelli Internal Officer: Gülin Keşmer PR Officer: Augusta Mateescu

Peer Review Panel Ana Elena Martínez Rodriguez Carlotta Drewer Ekin Zeki Lotte Wayenberg Panagiota Tsoutsa Ruben Feddes Yehia Hamadi

Illustration and Graphics Team Bogdan Toader Justine Laus Spoorthi Acharya Yuliia Niehanova The Honours Review is a student publication by the Honours College of the University of Groningen, the Netherlands.

We thank our reviewers, authors, and artists for their incredible work and support in making this issue. We also extend our gratitude to the Honours College team of the University of Groningen for their help and financial support.

For more information visit: Website: honoursreview.com Instagram: @honoursreview To contact us via email, please use honoursreviewrug@gmail.com p-ISSN 2214-6083 e-ISSN 2214-6466

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