WINTER 2017
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Staff Co-Editor-in-Chief
Miriam Heard
Co-Editor-in-Chief
Rose Strickman
Academic Editor
Candy Boerwinkle
Creative Editor
Anastasia Tucker
Copy Editor
Alanna McAuley
Blog Editor
Erin Nettifee
Designer
Jyothirmayee Mocherla
Publicity Coordinator
Huda Shaltry
Peer Reviewers Victoria Rahbar Anamika Soni Circulation is the student-run journal of the Information School at the University of Washington. We seek to foster and publish student creative expressions and academic work. We also support student interest in literature, scholarly communication, and publishing through special events and
MISSION STATEMENT 2
from the
Editors
In the wake of the last year, and even the most recent months of 2016 into 2017, there could not be a better time for Circulation to come together with all of the iSchool, all of UW as a whole, to celebrate and recognize diversity. We are fortunate to be a part of an institution that fosters growth and collaborative efforts. Circulation is forged from many walks of life, and as a result, we are able to share with the iSchool, some of the amazing creative and analytical works of our peers. In the current climate, and in the wake of violent events on our own campus, these works, and the celebration of diversity and ideas, are more important than ever. This academic Issue marks another example of how robust the iSchool student body is in the exchange of ideas and solutions to challenges in the community. We can all do great things with the wonderful education we have from the iSchool, and our varying perspectives and experiences that shape our outlook on life. We should not take for granted the opportunities we are afforded, or forget that there are many others who do not share them. We can set the tone for the future and promote and instill our dedication to inclusive spaces, to welcome a new generation of diversity. Circulation would like to thank you all for participating in our thrice annual Call for Submissions. Without your impactful work, we would not be able to highlight the progressive contributions we make to the literary world. As the current crew signs off, we want to express our sincerest pleasure in being able to work on this issue, and extend our warmest welcome to the incoming Circulation staff for 2017-2018.
Miriam Heard
Rose Strickman
Circulation, Co-Editor-in-Chief
Circulation, Co-Editor-in-Chief
MLIS Candidate
MSIM Candidate
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CONTENTS
Information Behavior of Cam Models
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Professional Networking in a
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Multicultural Environment Gender Portrayal in Video Games: A Look into Gender - Swapping
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Information Behavior of Cam Models By Katiana Yeo | Katrina Gertz | Lou Wainer | Megan Mitchell | Nicole Sonett | Samantha
A cam model is a paid performer that entertains viewers on the internet in real-time, often but not necessarily engaging in sexually explicit activities. Most of the literature on this industry comes in the form of investigative journalism , and has only recently started to 1 appear in academic literature, mostly in relationship to feminist theory or digital anthropology. Given the independent nature of camming,
where performers take a central role in managing, promoting and producing their own content, we set out to study this industry through the lens of information science, examining the information needs, information seeking behaviors and information sharing culture of cam models. We investigated different aspects of this industry, inspired by the theoretical frameworks of Chapman’s Small Worlds and Insider/Outsider behaviors, as well as perspectives in anthropological, sociological and feminist theory. To supplement the lack of relevant academic sources, we deepened our understanding through more informal sources of information such as reddit, forum discussions, terms and conditions from various camming websites, and other resources directed to or compiled by cam community members. We were particularly interested in their conceptualization of privacy and the measures taken
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to guarantee online security. Our research focused on methods and communication tools associated with obtaining informed, up-to-date information on safety practices. To examine the information behavior of cam models, we conducted three semi-
structured in-depth interviews and applied a survey created in Google Forms. The interviewees ranged in backgrounds and stages of their careers: “Kaitlyn” , a former cam girl 2 who worked for around six months on My Free Cams, “Lori” a cam model involved in different forms of sex work for over 20 years; and “Sana”, who has only been modeling for five months. The survey was posted on previously identified websites that focus on providing support for cam models: the forums
Ambercutie, Stripperweb and We Camgirls; targeted Facebook groups and Tumblr pages belonging to cam models. Models use various online platforms to find and share information about the profession, although the prevalence of forums as the main informational tool may be a biased conclusion since the survey was posted on camming discussion boards. Different platforms are used depending on the information need: models will use
Twitter or other cam sites for business related information (publicity and what to charge, for instance), and forums for information on online security and work ethics. Membership validation seems to be the biggest detriment to the forums, since new members don't have access to all content.
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Selected Bibliography 1. /r/camming. Accessed February 11, 2016, from https://www.reddit.com/r/ camming/.
2. /r/sex. Accessed February 11, 2016, from https://www.reddit.com/r/sex/. 3. AmberCutie’s Forum - Where cam girls and fans can discuss all things! 2016. Retrieved from https://www.ambercutie.com/forums/ 4. Bleakley, Paul. April 16, 2014. “‘500 Tokens to Go Private’: Camgirls, Cybersex and Feminist Entrepreneurship.” Sexuality & Culture 18, no. 4: 892–910. doi:10.1007/ s12119-014-9228-3.
5. Cam Girl Wiki. 2015, March 5. Retrieved from https://www.camgirlwiki.com/ 6. Chatman, E. A. 1996. The Impoverished Life-World of Outsiders. Journal of the American Society for Information Science, 47(3), 193–206. 7. Dunne, Sean. 2015. Cam Girlz. Retrieved from https://vimeo.com/155155963. 8. Hearn, J. 2008. Sexualities Future, Present, Past . . . Towards Transsectionalities. Sexualities, 11(1-2), 37–46. http://doi.org/10.1177/13634607080110010205
9. Hearn, J. 2008. Sexualities Future, Present, Past . . . Towards Transsectionalities. Sexualities, 11(1-2), 37–46. http://doi.org/10.1177/13634607080110010205
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10. Live Web Cam Best Practices. 2014, August 27. Retrieved from http:// www.webcamlaws.com/live-web-cam-best-practices/ 11. Saraswati, L. A. 2013. Wikisexuality: Rethinking sexuality in cyberspace. Sexualities, 16(5-6), 587–603. http://doi.org/10.1177/1363460713487368 12. Shields Dobson. 2008. “Femininities as Commodities: Cam Girl Culture.” In Next Wave Cultures : Feminism, Subcultures, Activism, edited by Anita Harris, 123–48. Critical Youth Studies. New York, NY: Routledge. 13. Stöckl, Andrea. 2003. “The Internet, Cyberspace, And Anthropology”.Cambridge Anthropology 23.3: 67–78. 14. Wilson, S. M., & Leighton C. Peterson. 2002. The Anthropology of Online Communities. Annual Review of Anthropology, 31, 449–467. Retrieved from http:// www.jstor.org/stable/4132888 15. “AdultWork.com - Terms of Use.” Accessed February 7, 2016. https:// www.adultwork.com/dlgTerms.asp. 16. “Code of Conduct | Streamate Webcam Models.” Accessed February 7, 2016. https://www.streamatemodels.com/conduct.php . 17. “Rules and Guidelines - Wiki.MyFreeCams.com.” Accessed February 7, 2016. http://wiki.myfreecams.com/wiki/Rules_and_Guidelines. 18. “Terms & Conditions - Chaturbate.” Accessed February 7, 2016. https:// chaturbate.com/terms/.
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Professional Networking in a Multicultural Environment By Eric McAweeney | Yun Wu| Kushal Shah| Gaurav Gada
Abstract This research looks at the challenges students face in a multicultural professional networking environment. While the global markets and workforces continue to become increasingly more globalized, little to no research has been conducted to investigate a diversifying professional networking landscape and its effects on students. The study draws upon both qualitative and quantitative methods to better understand the cultural barriers that are most likely to affect a student’s professional networking interaction. Qualitative analysis was first conducted to parse out the factors contributing to multicultural networking challenges most commonly shared among students. Secondly, based on these factors, a survey was administered to quantify the prevalence and strength of these barriers as experienced by students of different nationalities. This study’s findings identify and detail prevalent cultural barriers students face in a
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multicultural networking environment. Results show a strong connection between cultural barriers, especially language and cultural knowledge, and a student’s comfort level in a multicultural networking scenario.
Introduction There are countless examples representing the ways sophisticated information communication technology has had astounding impacts on the global market and workforce structure. Professionals are connecting instantaneously and crosscontinental operations can flow with unprecedented ease. Executives are now looking beyond their country’s borders for new opportunities to acquire companies, outsource work to, and recruit fresh talent. These transitions are not isolated to the workforce – changes are noticeable from the nascent stages of a professional career. The increasingly diversifying population of university students speaks to a growing foundation of an interconnected, multicultural workforce. The intention of our research is to gain a better understanding of the challenges students face in a multicultural, professional networking environment, to not only help students better navigate a foreign landscape, but also strengthen the bedrock of a global economy.
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As we know, making professional connections and networking the business playing field is a vital tenet of a higher-education degree, and the quality of a single interaction can make or break an employment opportunity. There are many pieces of literature available that outline the “do’s and don’ts” of professional networking strategies, but current guides fail to consider the effects of a globalizing applicant pool and the new complexities a convergence of diverse backgrounds creates. Rather than continuing to enforce this “one-size-fits-all” mold in networking styles, educating students on their differences and strengths will encourage mindful, intentional interactions in a professional environment. This study explores the varied styles of professional networking, influenced by various cultural backgrounds, present in an ever-increasing multicultural networking environment. We inspect several elements of professional networking including those from previous studies, such as language, cultural norms, cultural knowledge, group dynamics, and values. Significant studies have been undertaken to help professionals and students network effectively in business environments and several have been endeavored to help them manage multicultural work-forces. But, there is not enough literature available when it comes to helping students network in a multicultural environment. Many existing articles, such as “Understanding the
importance of Culture in Global Business,” [1] declare the importance of knowing how to do business across cultures. According to the article, the ability to leverage the power of culture is decisive in a company’s success in this increasingly global market. However, it doesn't mention how to network in this diversifying job market,
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which is an important first step into the workforce and a critical component in entering the cross-cultural world. Van Hoye, G.et al [2] explores social network considerations on networking and outcomes. This work aims to further understand peculiarities of social networks among people from different cultural backgrounds. Similarly, we aim to look at cultural origin as an influencing factor on networking, but will expand this notion to professional outcomes. Another work[3] studies professional communication between different groups of people, addressing communication between different groups as very important in their professional life. Although the book included the professional communication between groups of different cultural backgrounds, it is mainly significant for sociolinguistics and foreign language teaching instead of people looking to enter the professional field.
The existing research is mainly isolated to conflicts already occurring in a workplace; our study will be more focused on the professional communication during networking with the intention of finding a job or
internship, making research more applicable to entry-level students. Method Interview: The method used for conducting interviews was Quota and Convenience Sampling; we selected an equal amount of people from the 3 different cultural backgrounds to be interviewed. Emphasis was given to consider cultural diversity
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into account and to avert expected results. As a methodology, we followed Critical Incident Technique (CIT) - where we tried to understand challenges the participant might have faced with regards to networking with someone from a different cultural background. This eliminated research’s bias since the participant chose an experience which is suitable in the given context. Also since CIT didn’t provide a specific framework to participants - so they had the liberty to respond in ways that were more convenient to them. The instrumentation for our interviews is included in the appendix. The interview preceded the survey to provide further references for the questions. The interview was conducted in an informal but private setting where the participant was comfortable to share unbiased opinion and also all participants were incentivized with snacks as a token of appreciation. We took notes and recordings during the interview after taking necessary permissions from the participants. Also, participants reserved the right to walk away from the interview or retract a statement as per their convenience. Survey: The survey method was Quota Sampling where we tried to ensure that a balance is maintained between people from different cultural backgrounds. Three major cultural backgrounds were explored for the scope of this project i.e - American, Chinese and Indian students. Survey questions were formulated using Google
Forms and were sent through email. Responses to the survey were stored in a Google Sheet, so to ensure anonymity. Also, responses were normalized according to the participant’s nationality such that a balance is maintained between different cultural backgrounds.
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The survey questionnaire was structured to assess factors inhibiting the participant’s ability to network effectively (if any). In all thirteen questions were asked, so to ensure that participants engage and answer questions truthfully. Questions were designed in a way to prevent the surveyors from identifying the respondent. The survey was aimed at understanding the perspective of the participant when the participant faced a cultural barrier while networking. Our questions were based on the results of the qualitative analysis of our interviews. The questions of the survey mainly included the interpretation of the participant’s background, and the language barrier, cultural norms barrier, and cultural knowledge barrier that a participant might have faced during a networking event. We included the instrumentation of our survey in the appendix. Sampling Procedure, Selection of Subjects Sampling for the interview: We sent emails to 6 prospective interviewees chosen based on convenience. These interviewees included 2 Chinese students (1 first year, 1 second year), 2 Indian students (1 first year, 1 second year), and 2 American students (1 first year, 1 second year) expecting that quota can be filled for the interview sampling. The email included: a. The topic of the interview b. The way in which the information is going to be used c. When the information will be destroyed The email also informed them results of the research will be shared with them and
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food will be provided during the interview. Fortunately, all of these 6 subjects agreed to participate in our study by agreeing to meet for an interview. Sampling for the survey: We designed a questionnaire of 13 questions based on the qualitative analysis of the transcriptions. We formulated the questionnaire through Google Form. We sent out emails that include the address of the Google Form and the informal consent to 45 MSIM students. We tried to do quota sampling so that we included 15 Chinese students, 15 Indian students, and 15 American students to balance the number of students from different cultural background. The informed consent includes: a. The purpose of the survey b. How long it will take to complete the survey c. The participation is totally voluntary d. The responses will be entirely anonymous e. Contact information of our team members Through the informed consent, we got the subjects’ ethical approval before they start answering the survey.
Data Collection Procedure Data collection for interview: We conducted the interview according to interviewees’ convenience both time-wise and location-wise. In order to create a comfortable environment and rapport with interviewees, we did our best to match the interviewer and interviewee nationality, as our subject matter will address potentially sensitive cultural-specific content. During the interview, we took notes and recording with an audio recording application on phone and by computer as a backup. Each interview was finished within 30 minutes. After the interview, we transcripted the content of the interview.
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Data collection for the survey: After we sent out emails to those 45 students including 15 Chinese students, 15 Indian students, and 15 American trying to do quota sampling, however, there were only 11 responses . Thus, we sent out a reminder 2 days later and expanded our sampling pool by including 93 more potential participants. We sent out another reminder 2 days later. In the end, we received 36 responses in total, including 18 responses from American students, 10 responses from Indian students, and 8 responses from Chinese students. Because of the unbalance of the number of the students from different cultural background, we decided to use these 36 samples we collected.
Validity and Reliability Initially, we sent our 45 emails - 15 each for US, Indian and Chinese nationals and got only 11 responses. The second set of email were sent to 94 emails and additional reminders were sent to the original sample. At the end, we got 36 responses (18 US, 10 Indian and 8 Chinese). Hence, the survey responses were not evenly distributed across nationalities. We would have wished to get more responses evenly distributed across the 3 nationalities. Moreover, our findings are based on a sample size of 36 participants. A larger sample size would have made our findings more reliable.
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Ethical Considerations We ensured `respect for persons’ by ensuring that our survey and interview participants are adequately informed about potential risks and have the right of selfdetermination. After informing them about our research methods and topic of research, we allowed them to decide if they want to opt-out of the study. We ensured they are given a comprehensive overview of the research through a survey prompt or verbally (in the case of interviews). The details of our study were provided to participants in a way that is easily understandable to them, As our research sample consists of graduate students, we assume they are fully capable of self-determination. Only once we got voluntary participation, we continued with the survey and/or the interview. We also provided means to address any questions that our participants may have about the research study. Hence we applied the concepts of `information’, `comprehension’ and `voluntariness’ pertaining to `informed consent’ as per The Belmont Report[1]. Our research involves surveys and interviews and touches upon a topic (networking and job search) which could be a cause of stress for our participants. We did not ask probing questions such as “Did you manage to get a job after that networking interaction?”, “Do you have a fulltime position now?” Our questions focused only on networking interactions and not
on sensitive outcomes. We focused on relations between elements of culture and diversity on networking transactions. We were also mindful by avoiding culturally sensitive topics. Through this approach, by `maximizing possible benefits and minimizing possible harms’, we remained `beneficent’ towards our research
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participants. We ensured `justice’ by selecting students from the graduate school cohort and sharing our findings so that they may use it for their benefit. We took permission from the participants about publishing findings based off of their data. If someone didn’t agree, we did not collect information from them, thus respecting their free choice. The data collected through the surveys was collected anonymously through a web-based survey form mechanism. We thus addressed any student privacy concerns that may arise. The data collected in interviews enabled us to personally identify individuals but we ensured that we do not publish the results in a way that would compromise the anonymity of our interviewees. Our project team would be working with completely de-identified data. Further, we ensured that we do not collect any private information prohibited by law. The consent for this research was taken verbally for the interview and on a web interface for the survey. The consent form is included in the appendix. On this screen, the participants were able to give consent or reject to participating in our research.
Analysis & Findings Method of Analysis Our Method of Analysis is divided into Qualitative and Quantitative parts. Qualitative Analysis As we utilized the Critical Incident Technique to elicit narratives of multicultural networking experiences from people,
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we found it most effective to employ a mix of narrative and thematic analysis to understand how people talk about their multicultural networking experiences. Narrative analysis focuses on extracting the common narrative structure (i.e. the “twists and turns”) that share a common thread throughout subjects’ critical networking incident experiences. While this analysis yielded variables such as “affected outcome” and “comfort level” narrative structure alone did not suffice for a full representation of the themes present in the interviews. Subsequently, we chose thematic analysis as this offered a broader scope to identify themes. As our qualitative research was used to inform the quantitative analysis portion of the study, and since our approach was a mix of inductive and deductive, these two forms were used to identify potential new variables and clarify definitions of existing variables. Our initial reader identified a comprehensive list of themes and codes within these themes, and a second reader added additional themes and codes that were not already present in the analysis. Through the analysis, we uncovered new variables and found new dimensions of our existing variables. All interviewees, regardless of nationality, identified specific incidents of multicultural networking interactions and spoke to the positive or negative effect cultural barriers had on the outcome of the interaction. Language was the most predominant among the cultural
barriers listed by Indian and Chinese students, especially vernacular and accent. Surprisingly, personality was also a common theme throughout interviews that students believed to be an aspect of multicultural networking. While it is important to indicate the presence of this variable, we ultimately decided to omit it from our
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quantitative study as it would be too complex of a variable to use for the scope of this study. New codes within cultural norms were brought up by interviewees and expanded our definition of this variable to include customs/traditions and networking style. Based on the interviews and analyses the codes knowledge of popular sports and knowledge of current events were added to the cultural knowledge variable as well. The suggestions made throughout interviews inspired us to create an open-ended question at the end of the survey asking participants to detail what they could have done differently to lessen the cultural barriers in their networking interaction.
Themes & Codes Language:
Code
Example
Vernacular
“the jargon they use is very different than in India”
Accent
“it was difficult to understand their accent”, “he did have a heavy accent”, “there were accent barriers”
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Cultural norms: Code Customs/Traditions
Example “very family oriented cultural background”, “in office spaces we are very open with our team members and we make friends very easily”, “I faced a cultural shock”
Networking Style
“in India we have a lot of respect for each other if I am working with a supervisor or a manager”, “It’s different when you are talking to supervisors and seniors and when you are talking to your colleagues”, “The difference that it made was that people used to talk to their manager like they were their friends while back in India we had this barrier sort of thing that you respect your manager and you
don’t directly go and talk to him” Networking process
“If you are seeking a job and you are talking about networking and you are in India, it’s basically a 1-1 communication that you have with the HR”, “Networking is different in China. You don’t reach out to random people. There is a set of relationship between people and they help you get jobs.”, “For getting any jobs, you go through a basic interview process and there are no social networking events that happen, which is quite different than in USA”
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Cultural knowledge: Code
Example
Knowledge of a pop- “common movies and common events that were happening ular sport/hobby
around UK”, “you have to talk about the football game in America”, “people are talking about football if she is aware about the cultural knowledge, she could engage in a small
Knowledge of Cur-
“update myself you know read newspapers and get to
rent Affairs
know some topics”
Personality: Code Introvert
Example “I regard myself as an introversive person”, “Because I'm an introversive person. I'm always feeling embarrassed, I'm
always feeling struggling. Whenever I went to any networking event. Especially I have to talk to those professionals and pretend to be very excited, pretend to be very professional.”, “not a social person” Extrovert
“I’m a very outgoing and talkative guy”
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Affected Outcome: Code Positive
Example “changed the nature of the interaction between us”, “I don’t think I’ll be interviewing with Adobe anytime soon”, “In this particular case this individual was from a different culture and that influence how the conversation went negatively”
Negative
“I think I did that pretty well”, “it turns out to be a good result”
Comfort:
Code
Example
Comfort level
”it was simpler to talk to people from your own culture
of networking
than talking to people from other cultures”, “Reached to
interaction
Chinese recruiters or managers, so that they understand the barrier that she might be facing...they can provide moral support too”
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Suggestions Code
Example
Prior to networking
“communications meetup every quarter so anyone could go
interaction
up and talk about their experiences”, “you try out things initially, with your friends or make up your mind, visualize things like how it’s going to happen at the networking event, what are the questions you are going to ask and with the language and the accent and all those things, once you get used to it you’ll be better at it.”, “reach out to people and not be hesitant. Participate in communities. Talking with native English speaker - learn naturally”
During networking
“talk 1-1”, “do not panic”, “while trying to initiate a conver-
interaction
sation be very mindful about the topics you are going to be talking on, don’t choose politically sensitive topics at all and maybe in order to network well with maybe foreign students or people with other countries, it’s better to know their cultural background as well so that something com-
mon to talk about”, “be confident, and be yourself”
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Quantitative Analysis Based on the qualitative analysis, we came up with a survey (see Appendix: Questionnaire). The survey was sent out to 60 email addresses and got 36 responses (60% response rate). The responses to our survey lead to the following quantitative analysis. The above graphs illustrate the distribution of the responses in the form of a bar plot for a few questions relating to our variables networking comfort and networking outcome. The method of analysis followed was cross-tabulation and chisquared tests.
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Our survey contained demographic variables such as the country the participant has lived in for the past five years, native language, introduction to English, their English-speaking ability, sex, and their comfort in networking interactions. Initially, we analyzed how a participant’s demographics affect barriers they faced during Also, Chi-Square analysis was conducted with respect to demographic variables (independent) and the dependent variable i.e. Outcome variable. Here all the demographic variables were nominal and the outcome variable was converted from Likert-scale to an ordinal variable. The analysis was conducted by developing pivot tables and then calculating the inverse chi-square. The resultant chi-square was compared with critical values in order to reject or accept the null hypothesis.
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networking interactions. The networking barrier variables were ranked and participants were asked to rank the barrier they faced. Also, participants had an option to not rank the barrier in case it did not apply to them. We then tried to find patterns between demographic variables and the networking barriers where we assigned calculated the sum of ranks with every demographic variable. A score of ‘four’ was assigned to ‘Does not apply’ indicating that this particular barrier was least for this participant. However, we realized that the distribution in our survey was skewed and hence had to normalize our findings. Here, we divided the calculated sum by the number of instances for that particular demographic variable.
Data Screening Reliability Testing Since we got very few responses, we did not screen the data and used all the data that was available. In the networking barrier variable, there was a ranked-option called Does Not Apply and instead of discarding those instances - we decided to give a rank value of four for our analysis
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Pattern Analysis Results
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Some examples from our analysis are: The pattern analysis done with respect to networking barriers indicates patterns such that participants whose native language is English face minimum number of networking barriers, followed by participants whose native language is Hindi and lastly Mandarin speakers perceive that they face the most number of networking barriers. The same could be reflected when Nationality is our input variable. Participants from China face the most amount of barriers and participants from the USA the least. The variable age to start learning English could also indicate that participants who have started learning English from the very beginning – face the least amount of barriers. Whereas the variable sex could not demarcate patterns between Male and Female respondents. We did not have any participant who choose not to answer or who chose the ‘other’ option for this variable.
Chi Square Results
Independent
Dependent
Variable
Variable
Sex
Result
Outcome of
The chi-square result is 1.71 with 3 degrees of
networking
freedom and hence we reject the Null Hypothesis
session
with 90% confidence.
Native Language Outcome of
With 5 degrees of freedom, the chi-square value is
networking
14.71 and hence we accept the Null Hypothesis
session
with 90% confidence.
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Independent
Dependent
Variable
Variable
Result
Country of
Outcome of
With 6 degrees of freedom, the chi-square value is
Origin
networking
22.309 and hence we reject the Null Hypothesis
session
with 99% confidence.
Age when intro- Outcome of
With 9 degrees of freedom, the chi-square value is
duced to English networking
49.1 and hence we reject the Null Hypothesis with
session
99.99% confidence.
Conclusion Interpretation When addressing our research topic—what are the challenges students face in a multicultural professional networking environment—these results add new dimensions to our understanding of the globalizing professional networking landscape. This study allowed us to draw connections between the types of cultural barriers most common in professional networking and the students that are most affected by these barriers. As we expected, our qualitative and quantitative results indicate clear correlations between a student’s perception of a cultural barrier and a perceived influence on the outcome of the networking interaction. Our results also illustrate the most common cultural barriers (such as language) and the various aspects of a student (nationality or native language, for example) which make an individual more likely to encounter these challenges (our results indicate Chinese students feel most hindered by a language barrier, as
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indicated in our findings). The ranking style of the survey gave us better insight on what the least and most prominent barriers are and how influential these barriers are on an overall professional networking interaction. Based on this study, many students feel challenges within a multicultural professional networking environment, yet training and literature are not available to help navigate this environment. These findings offer important insight for evidence-based multicultural networking training for students. Identifying these challenges will help students not only better understand the barriers they face in a structured manner, but also better informs us on how we can improve the experience and skills of students entering a globalizing professional networking field. While further research should be done before developing curriculum, this study has indicated communication skills and basic cultural knowledge as prevalent barriers which students need guidance developing. This study also lays out a framework and vocabulary for further research on multicultural networking, especially important interpretations and elements involved in cultural barrier variables which emerged from our qualitative analysis. We found the process of first conducting interviews using CIT and qualitative analysis to identify specific barriers and better define these barriers followed by a survey based on these results was very successful. We encourage future studies to adopt this framework for future research on the multicultural networking landscape.
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Unexpected Outcomes 72% of our participants also responded that they were more comfortable to network with someone from a similar cultural background as themselves. This shows a lack of comfort to network with individuals from a different cultural background. By analyzing sex with networking barriers - we found no association between sex and the networking barriers faced whereas the chi-square analysis suggests that a person’s sex can help suggest the networking outcome. Native language was a clear indicator to suggest the amount of barrier the participant can face - but in terms of networking outcome, the same is irrelevant. Our interpretation is that subjects perceive interviews as more skills based i.e. the interviewer would focus more on the skills the participant has rather than their native language.
Limitations The study was aimed at understanding challenges that people could have faced
while dealing with people from other cultural backgrounds, but the majority of participants interviewed had limited multicultural networking experience. Also, there was no way to assess how closely the responses of both the interviews and surveys were reflective of subjects’ experience or if they were filtered through a subjective bias. Also, the survey respondents were not an actual representation
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representation of the Information School’s MSIM program since there were more American respondents and this sample isn’t reflective of the whole MSIM program population. We tried to balance our sampling, but ultimately did not discard and responses to stratify our sample size as we decided quantity was more important for our analysis. Also, with respect to networking barriers, some participants misunderstood the ranking process and gave the same rankings multiple times. We can avoid such confusions in future by more clear explanations on our survey questions.
Future Scope Results from this study make a case for future study on the topic of multicultural
networking. Also, the analysis was undertaken having only one independent variable, and a more accurate and in-depth analysis could be made by considering multiple dependent and independent variables. We did not have multivariate analysis available to us in this study, but strongly recommend it for future work. We also hope future scope for this research topic will include multicultural networking in different environments outside of the U.S.
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References 1. United States. (1978). The Belm o nt report: Ethical principles and guid elines fo r the protection of human subjects of research. Bethesda, Md.: The Commission. 2. Hummei, D. P. (2012, May). Understanding the Importance of Culture in Global Business. Retrieved from http://www.oracle.com/us/corporate/profit/archives/ opinion/050312-dhummel-1614961.html 3. Van Hoye, G., van Hooft, E. A. J. and Lievens, F. (2009), Networking as a job search behavior: A social network perspective. Journal of Occupational and
Organizational Psychology, 82: 661–682. doi:10.1348/096317908X360675 4. Scollon, R., Scollon, Suzanne Wong, & Jones, Rodney H. (2011). Intercultural Communication : A Discourse Approach. (3rd ed., Language in Society). Hoboken: John Wiley & Sons.
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Gender Portrayal in Video Games: A Look into Gender - Swapping By Elizabeth Duong | Royce Le| Tanner Garrett| Soichi Tanabe
Abstract When a player interacts with others in a video game, who is the player actually interacting with? Behind a screen where others are unable to see them, players are able to choose and play as different characters in a virtual world. A male player could choose a female character to portray as, and may even take on a female identity when interacting with others in the game. There could be many various reasons for why someone would choose to play as the opposite (or same) gender. Our research attempts to answer the following question: In gaming, do more people choose characters of the gender they were assigned at birth? We specifically focused on video games, as individuals are able to choose and portray their self as a character in a video game.
Keywords Video games, gender, character selection, identity, representation, diversity, identification, character.
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Introduction In order to begin discussing our study in depth, it is important to solidify a working definition of the following keywords in our research question: “video game” and“virtual world.” Although there are many definitions for the words we are defining, we chose the definitions based on an easy of understanding. To get started, we define video game as “an electronic game played by means of images on a video screen and often emphasizing fast action.” [5]. Next, a virtual world is a computer-based online community environment where users interact with each other in the simulated world using text-based, two-dimensional or threedimensional graphical models called avatars [6]. With these working definitions, we may appropriately proceed with discussing our study. Our research question is as follows: “In gaming, do people choose characters of the gender they were assigned at birth?” The motivation for our research comes from our deep interests of video games. Moreover, our research question was inspired by
an Immersive Environments class at the University of Washington, where our professor prompted us with a new outlook on how to look at virtual world and avatars with social implications. Those factors were what made us think about how gender and identity plays a factor in video games.
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To tackle our research question, we surveyed a random sample of Internet users from various Facebook and Reddit groups. We received 182 responses, 143 whom were assigned male at birth and the remaining 39 respondents were females. In addition, we conducted 20 interviews total with randomly selected participants who provided us with their contact information in our surveys. Our key findings in our study suggest that a majority of both males and females prefer to pick the same gender when playing video games and the reasoning behind doing so has a vast range, some of which are covered in related works. Related Works Studies in the field of gender research have been conducted for centuries, but in the recent 100 years, there has been a marked point of significance in gender research with the establishment of the journal Sex Ro les [7]. Research on gender development and understanding in the physical world has been the main focus for many years, it was only in the past decade and a half where the video game boom happened, thus, an increase in research about gender in the non-physical world, specifically, games [4]. One study conducted by three researchers from the Department of Psychology in Oklahoma State University found that “male characters were almost four times more frequently portrayed than female characters and were given significantly more game relevant action found that male character were often more playable than female characters� [1]. Therefore, girls might be prompted to choose male just because of relevancy and significance of role. Another study found that males in
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video games are often less sexualized than female characters, thus a possible reason for males to pick females, because of looks [2]. There are more studies around the social implications of gender in video games, but, through exploring literature, we in found that the work most similar to ours is a study called Gend er Swapping and Socializing in Cyberspace: An Exploratory Study [3]. Like our work, this research had subjects complete a survey on their feelings and opinions on games and gender. How our contribution differs is that we’re talking about more than just MMORPGs but a wide variety of games in addition to conducting anecdotal interviews as opposed to just questionnaire. Overall, our research will contribute to a gap in knowledge about people’s perception, thought, and feelings on a deeper level about gender swapping for people in many mediums of video games.
Methodology We utilized both online surveys and in-person interviews in order to gather
information on male and females’ gender choices in video games. Our rationale behind choosing only male and female participants is based on a criterion is called sex-assigned-at-birth and is purely a biological distinction. The more descriptive and complex construct of gender could be used in more sophisticated research projects, but for the purpose of our study, we’ll keep the construct of gender simple.
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In our survey, participants were asked to answer questions about video game use, preference, character gender choice, and current demographic information. Each participant took the same survey on their own devices remotely with no time limit allotted and the ability to opt out of any question. Participants: The participants in our study ranged from many different demographics. There were 182 participants who filled out our survey, of which, 143 were assigned male at birth, and 39 were assigned female at birth. Moreover, 77.9% of our participants were 18-24 years old. Since our survey was conducted over the Internet, our participants could have come from all over the world. Surveys: From our surveys, the information we gathered was quantitative data about the gender of the participants at birth, the gender they identify with, and the gender they generally choose in a video game. We wanted to make our survey short and simple to get as many respondents to complete our survey. We followed the standard survey conventions and placed the demographic questions at the end so as not to deter participants from our survey. While we collected every respondent’s data, we screened out participants that did not play video games and have the survey skip the additional questions relating to video games. We spent time looking at each question to ensure none were framed in a leading or biased way and made sure the options for the multiple choice questions covered all possible answers our respondents may have had.
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Figure 1. Charts of distribution of character gender choices based on gender
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Google Forms automatically generated some visual charts for us but they didn’t have the exact data they were looking for. To analyze our surveys, we needed to wrangle the data in the CSV (comma-separated values) file generated with the Google Forms. We wrote a script with node.js that grabbed data from the CSV file and gave us every combination between the gender chosen and the gender of the participants at birth. With these new numbers, we were able to input them into another excel file to create various charts to visualize our data. We created a bar chart to see the distribution of the respondents who took our survey based on gender they were born with. Another bar chart displays the number of respondents that choose the same gender vs the opposite one when choosing a character. Our last two surveys show the percentages of the different genders chosen for males and females. Before distributing our survey, we pilot-tested the survey with six of our friends before finally distributing the survey. The survey was released in various University of Washington Facebook groups, the Informatics for Undergraduates Association Facebook group, and the subreddit “SampleSize� on Reddit to get a random sample. We initially distributed our survey only once to each location, and kept it open for exactly two weeks for anyone to respond. Interviews: We conducted 20 interviews total with randomly selected participants who provided us with their contact information in our surveys. The interviews averaged around 30 minutes and included 16 questions total that went into more
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depth about the reasoning behind certain choices that our surveys could not grasp. Our interviewer also went off script when needed to probe into areas that were relevant and interesting. We were also able to go back to the immersive environments class to interview one of the auditor students there. Although this individual was not randomly selected, he provided us with useful information because this class covers questions like identity and avatar selection. His expert opinion was invaluable in providing context we could use to approach coding the information we received. During our interviews, some participants gave us the permission to record. For the participants who didn’t want to be recorded, we had one member from our team attempt to transcribe the whole interview directly onto his or her laptop. When we were given permission to record, we were able to go back to the video footage and rewind it to gather specific detail in certain parts of the interview. Apparatus The equipment we used for our interviews includes a computer and a video camera. The Camtasia Studio software was used to record computer screens for a few of our online interviews. To collect quantitative data, we used Google Forms as our survey platform as opposed to pen and paper or another survey tool such as Qualtrics. Google Forms is a survey tool developed by Google where administrators can
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manage event registration, whip up quick opinion polls, collect email addresses, gather research question responses, and much more. With Google Forms, we were able to create and analyze surveys right in the web browser so that no special software is required. The reasoning behind utilizing Google Forms as opposed to pen and paper is to outsource the hard work of data storage & upkeep and transcribing of data. In terms of survey platforms, we chose Google Forms to be the best one for our study purposes because Google Forms is a free software that nicely integrates to platforms that we use for compilation and analysis. Ultimately, the reason why we chose Google Forms as opposed to other survey mediums was for ease of use, convenience, and synchronous collaboration.
Design Our survey was created using Google Forms, and pilot tested by ourselves and peers within the Informatics program to eliminate as much bias as possible from the questions. Our peers were also in the same Research Methods class taught by Jacob Wobbrock, so they helped us in providing feedback and rewording our survey questions based on what we learned and read about in the class. It was then
deployed on Facebook to the Informatics Undergraduate Association group as well as the University of Washington Facebook groups for the classes of 2015 - 2018. In addition, it was posted to the community on www.reddit.com/r/SampleSize - an online space designed specifically for anonymous individuals from all
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demographics to post and take surveys for a variety of uses.
Results:
Assigned Male at
Assigned Female at
Birth
Birth
# of Participants
143
38
Character Chosen
89
5
35
26
Chosen Other
9
3
Identify as Male
140
1
Identify as Female
2
36
Identify as Other
1
1
Male Character Chosen Female
Data summary table of our survey results
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Data Analysis Out of the 182 respondents to our survey, 143 were male and 38 were female at birth. 115 of the respondents chose the character gender that was the same gender they were assigned at birth, 40 chose the opposite, and 12 chose other characters such as gender-neutral characters. Excluding the 12 participants that chose other and looking at the pool of the remaining 155 respondents, 74.2% of people chose the same gender they were assigned at birth. Broken down more specifically, 71.7% of males and 83.4% of females chose the same gender they were assigned at birth. Two of our survey participants indicated they preferred to choose female characters and were assigned as male at birth, but identify as female. Five of our survey participants chose to fill in the “Other” answer and tell us that they play “both” genders or is about “50/50”. As for our interviews, after gathering a
transcription of each interview, we
highlighted information that was directly relevant to the reasoning behind what participants based their character gender choices on. These highlighted segments were then written onto notecards and we coded these note cards into different categories based on different intentions of choosing a certain gender. The four categories we formed were skills, narratives, appearances, and social implications.
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Figure 3: The four categories formed when coding the reasoning for choosing a character
Discussion While a majority of users choose their own gender in video games, there are some that chose the opposite genders. Their reasoning could be due to a large number of reasons. From our responses received from our surveys, we were able to determine that 28% of males reported choosing female characters and 16% of females reported choosing male characters. Our coded interviews identified four main areas of thought that influenced individuals on what gender character to choose. The first concept we identified was the skills of the character. The category revolves around the gameplay elements of
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the character. When choosing characters based skill, the character was chosen depending on the innate skills or gameplay elements of the character as opposed to their gender. The second category of narratives identified the dynamic where a character’s gender changes the story of particular game. The choice of a character in this situation stemmed from the change in narrative the character and their gender brings about. Thirdly, appearance of the character is a characteristic that influences some individuals in which character they choose. In this category, individuals chose based on the visual aesthetics of the character - which could include gender. Lastly, social influences was a category that influenced participants in their choices. For example, one of our participants stated that they chose a female character to get different reactions from other players than if they had chosen a male character model. The two survey respondents that preferred female characters but were assigned male at birth may be due to the fact that they currently identify as a female. Playing as a female , they can relate and identify with their character, which other players will also see them as.
Limitations
From our blind survey approach, we acknowledge that there are limitations in our analysis due to not knowing the exact demographic information about individuals who decided to participate in our survey. Optimally, we would have distributed the surveys in a way that would ensure a more diverse spread of answers as opposed to
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posting them only on Reddit and Facebook, which greatly restricts the types of respondents we have in regards to only those that are on either Reddit or Facebook. The scope of our research was limited to only a small sample size of 182 respondents through our survey. With such a small sample size, we cannot generalize our findings to the general public, we can only speak to our data and results to say that in our study, people choose the same gender for their characters as the gender they were assigned to at birth. Future research should be done using other qualitative methods to expand on the reasoning behind people’s decisions. Conclusion From our interviews, we coded four main categories as to why people chose certain genders when choosing characters: skills, narratives, appearances, and social implications. As for our quantitative measures through surveying, females and males both choose the same gender they were assigned with at birth in a video game. Although we recognize as researchers that there are many limitations and confounds that limit our study from generalizing to a greater population, what we found in our study has real implications for the real world. Narrowing down the four main categories as for reasons why people choose their characters, knowing this, game designers could tackle those problems so that their male and female characters have equal representation. If game designers chose to increase female
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narratives and importance in games, then they could potentially increase female interest and support in the gaming world. All-in-all, with our study, hopefully people from all demographics can recognize the importance of representation.
References
1. Burgess, M.C.R., Stermer, S.P. & Burgess, S.R. Sex Roles (2007) 57: 419. doi:10.1007/s11199-007-9250-0 2. Friedberg, Jared, "Gender Games: A Content Analysis Of Gender Portrayals In Modern, Narrative Video Games." Thesis, Georgia State University, 2015. http://scholarworks.gsu.edu/sociology_theses/52 3. Hussain Zaheer and Griffiths Mark D.. CyberPsychology & Behavior. February 2008, 11(1): 47-53. doi:10.1089/cpb.2007.0020. 4. Nickson,
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http://
Palouse Falls State park, Washington submitted by Jyothirmayee Mocherla
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