The Potential Scientist’s Dilemma: How the Masculine Framing of Science Shapes Friendships and Science Job Aspirations
Abstract
:1. Introduction
1.1. Brief Overview of Theoretical Framing
1.2. Implicit Associations of Gender and Science
1.3. Stereotypes of Gender and Science
1.4. Norms and Friendships
1.5. Are Youth with Gender-Inconsistent Science Aspirations More Likely to Be Friends with Each Other than with Youth with Gender Normative Science Aspirations?
1.6. Statement of the Problem
2. Results
2.1. Do Boys and Girls Differ in Self-Assessed Science Potential, Reported Grades, and Career Aspirations?
2.2. Do Middle School Youth Believe Their Female Friends Are Science Kinds of People?
2.3. Are Youth with Gender-Inconsistent Science Aspirations More Likely to Be Friends with Each Other than with Youth with Gender Normative Science Aspirations?
3. Discussion
4. Materials and Methods
4.1. Survey Measures
4.2. Network Measures
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Network Structure Indicators | |
---|---|
Edges (volume of ties) | −7.526 *** (0.084) |
Mutual (both nominate) | 2.818 *** (0.079) |
Weighted shared friends | 1.196 *** (0.040) |
Demographic homophily measures | |
Both boys (base is different gender) | 0.811 *** (0.048) |
Both girls (base is different gender) | 0.900 *** (0.047) |
Same race (base is different race) | 0.275 *** (0.030) |
Same grade (base is different grade) | 2.035 *** (0.080) |
Same grade in science class (base is different grades) | 0.275 * (0.035) |
Same parental college attendance (base is different parental college status) | 0.024 (0.033) |
Science career homophily among boys (base is different career aspiration) | |
Both youth want a career: | |
that uses “A lot” of science | 0.303 † (0.158) |
that uses “Some” science | 0.209 * (0.097) |
that uses “A little” science | 0.228 † (0.133) |
that “Does not use any” science | 0.472 ** (0.155) |
Both youth “Do not know” | 0.040 (0.095) |
Science career homophily among girls (base is different career aspiration) | |
Both youth want a career: | |
that uses “A lot” of science | 0.526 ** (0.189) |
that uses “Some” science | 0.028 (0.072) |
that uses “A little” science | 0.065 (0.090) |
that “Does not use any” science | −0.103 (0.170) |
Both youth “Do not know” | −0.021 (0.078) |
BIC | 17629 |
Total number of students | 444 |
References
- Erin A. Cech, and Mary Blair-Loy. “Perceiving glass ceilings? Meritocratic versus structural explanations of gender inequality among women in science and technology.” Social Problems 57 (2010): 371–97. [Google Scholar] [CrossRef]
- Yu Xie, Michael Fang, and Kimberlee Shauman. “STEM Education.” Annual Review of Sociology 41 (2015): 371–97. [Google Scholar] [CrossRef] [PubMed]
- David Beede, Tiffany Julian, David Langdon, George McKittrick, Beethika Khan, and Mark Doms. “Women in STEM: A gender gap to innovation. ESA Issue Brief# 04-11.” 2011. Available online: http://www.esa.doc.gov/sites/default/files/womeninstemagaptoinnovation8311.pdf (accessed on 5 December 2014). [Google Scholar]
- Maria Charles, and Karen Bradley. “Indulging our gendered selves? Sex segregation by field of study in 44 countries.” American Journal of Sociology 114 (2009): 924–76. [Google Scholar] [CrossRef]
- Catherine Hill, Christianne Corbett, and Andresse St Rose. Why So Few? Women in Science, Technology, Engineering, and Mathematics. Washington: ERIC, 2010. [Google Scholar]
- Leslie Irvine, and Jenny R. Vermilya. “Gender work in a feminized profession the case of veterinary medicine.” Gender & Society 24 (2010): 56–82. [Google Scholar] [CrossRef]
- David Merolla, Richard T. Serpe, Sheldon Stryker, and P. Wesley Schultz. “Structural precursors to identity processes: The role of proximate social structures.” Social Psychology Quarterly 75 (2012): 149–72. [Google Scholar] [CrossRef]
- Amy C. Wilkins. “Race, age, and identity transformations in the transition from high school to college for Black and first-generation White men.” Sociology of Education 87 (2014): 171–87. [Google Scholar] [CrossRef]
- Sophia Catsambis. “Gender, race, ethnicity, and science education in the middle grades.” Journal of Research in Science Teaching 32 (1995): 243–57. [Google Scholar] [CrossRef]
- M. Gail Jones, Anne Howe, and Melissa J. Rua. “Gender differences in students’ experiences, interests, and attitudes toward science and scientists.” Science Education 84 (2000): 180–92. [Google Scholar] [CrossRef]
- Svein Sjøberg, and Camilla Schreiner. “A comparative view on adolescents’ attitudes towards science.” The Culture of Science: How the Public Relates to Science across the Globe 15 (2012): 200–13. [Google Scholar]
- Jennifer Blue, and Debra Gann. “When do girls lose interest in math and science? ” Science Scope 32 (2008): 44–47. [Google Scholar]
- Ming-Te Wang, and Jacquelynne S. Eccles. “Social support matters: Longitudinal effects of social support on three dimensions of school engagement from middle to high school.” Child Development 83 (2012): 877–95. [Google Scholar] [CrossRef] [PubMed]
- Jacquelynne S. Eccles, Sarah E. Lord, Robert W. Roeser, and Bonnie L. Barber. “The association of school transitions in early adolescence with developmental trajectories through high school.” 1997. Available online: https://www.researchgate.net/publication/233896223 (accessed on 26 January 2016).
- Jacquelynne S. Eccles, and R. W. Roeser. “Schools as developmental contexts during adolescence.” Journal of Research on Adolescence 21 (2011): 225–41. [Google Scholar] [CrossRef]
- Bonnie L. Barber, Margaret R. Stone, James E. Hunt, and Jacquelynne S. Eccles. “Benefits of activity participation: The roles of identity affirmation and peer group norm sharing.” Organized Activities as Contexts of Development: Extracurricular Activities, after-School and Community Programs, 2005, 185–210. [Google Scholar]
- Yariv Feniger. “The gender gap in advanced math and science course taking: Does same-sex education make a difference? ” Sex Roles 65 (2010): 670–79. [Google Scholar] [CrossRef]
- Elizabeth A. Gunderson, Gerardo Ramirez, Susan C. Levine, and Sian L. Beilock. “The role of parents and teachers in the development of gender-related math attitudes.” Sex Roles 66 (2012): 153–66. [Google Scholar] [CrossRef]
- Phillip M. Sadler, Gerhard Sonnert, Zahra Hazari, and Robert Tai. “Stability and volatility of STEM career interest in high school: A gender study.” Science Education 96 (2012): 411–27. [Google Scholar] [CrossRef]
- Julia McQuillan, and Myra Marx Ferree. “The importance of variation among husbands and the benefits of feminism for families.” In Men in Families. New Jersey: Lawrence Erlbaum Associates, Inc., 1997, pp. 213–25. [Google Scholar]
- Candace West, and Don H. Zimmerman. “Doing gender.” Gender & Society 1 (1987): 125–51. [Google Scholar] [CrossRef]
- Cecilia L. Ridgeway, and Tamar Kricheli-Katz. “Intersecting cultural beliefs in social relations gender, race, and class binds and freedoms.” Gender & Society 27 (2013): 294–318. [Google Scholar] [CrossRef]
- Brian A. Nosek, and Frederick L. Smyth. “Implicit social cognitions predict sex differences in math engagement and achievement.” American Educational Research Journal 48 (2011): 1125–56. [Google Scholar] [CrossRef]
- Raewyn W. Connell. Gender and Power. Stanford: Stanford University Press, 1987. [Google Scholar]
- Cecilia L. Ridgeway. “Framed before we know it how gender shapes social relations.” Gender & Society 23 (2009): 145–60. [Google Scholar] [CrossRef]
- Sapna Cheryan, Victoria C. Plaut, Paul G. Davies, and Claude M. Steele. “Ambient belonging: How stereotypical cues impact gender participation in computer science.” Journal of Personality and Social Psychology 97 (2009): 1045–60. [Google Scholar] [CrossRef] [PubMed]
- Allison Master, Sapna Cheryan, and Andrew N. Meltzoff. “Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science.” Journal of Educational Psychology 108 (2016): 424–37. [Google Scholar] [CrossRef]
- George J. McCall, and J. L. Simmons. Identities and Interactions: An Examination of Human Associations in Everyday Life. New York: Macmillan, 1978. [Google Scholar]
- Randal Collins. Interaction Ritual Chains. Princeton: Princeton University Press, 2004. [Google Scholar]
- Susan L. Williams. “Trying on gender, gender regimes, and the process of becoming women.” Gender & Society 16 (2002): 29–52. [Google Scholar] [CrossRef]
- Michael Lynch, and Dante Cicchetti. “Children’s relationships with adults and peers: An examination of elementary and junior high school students.” Journal of School Psychology 35 (1997): 81–99. [Google Scholar] [CrossRef]
- Wim Meeus, and Maja Deković. “Identity development, parental and peer support in adolescence: Results of a national Dutch survey.” Adolescence 30 (1995): 931–44. [Google Scholar] [PubMed]
- Jennifer A. Jewell, and Christia S. Brown. “Relations among gender typicality, peer relations, and mental health during early adolescence.” Social Development 23 (2014): 137–56. [Google Scholar] [CrossRef]
- Ronald S. Burt. “The network structure of social capital.” Research in Organizational Behavior 22 (2000): 345–423. [Google Scholar] [CrossRef]
- Julia A. Kmec, and Lindsay B. Trimble. “Does it pay to have a network contact? Social network ties, workplace racial context, and pay outcomes.” Social Science Research 38 (2009): 266–78. [Google Scholar] [CrossRef] [PubMed]
- Elizabeth H. Gorman. “Gender stereotypes, same-gender preferences, and organizational variation in the hiring of women: Evidence from law firms.” American Sociological Review 70 (2005): 702–28. [Google Scholar] [CrossRef]
- Louise Marie Roth. “The social psychology of tokenism: Status and homophily processes on Wall Street.” Sociological Perspectives 47 (2004): 189–214. [Google Scholar] [CrossRef]
- Dario Cvencek, Andrew N. Meltzoff, and Anthony G. Greenwald. “Math—Gender stereotypes in elementary school children.” Child Development 82 (2011): 766–79. [Google Scholar] [CrossRef] [PubMed]
- Huajian Cai, Yu LL Luo, Yuanyuan Shi, Yunzhi Liu, and Ziyan Yang. “Male = Science, Female = Humanities: Both implicit and explicit gender-science stereotypes are heritable.” Social Psychological and Personality Science 7 (2016): 412–19. [Google Scholar] [CrossRef]
- Miller McPherson, Lynn Smith-Lovin, and James M. Cook. “Birds of a feather: Homophily in social networks.” Annual Review of Sociology 27 (2001): 415–44. [Google Scholar] [CrossRef]
- Barbara J. Risman. Gender Vertigo: American Families in Transition. New Haven: Yale University Press, 1999. [Google Scholar]
- J. Miller McPherson, and Lynn Smith-Lovin. “Homophily in voluntary organizations: Status distance and the composition of face-to-face groups.” American Sociological Review 52 (1987): 370–79. [Google Scholar] [CrossRef]
- Barbara J. Risman. “Gender as a social structure theory wrestling with activism.” Gender & Society 18 (2004): 429–50. [Google Scholar] [CrossRef]
- Monica Gaughan. “Institutional assessment of women in science: Introduction to the symposium.” The Journal of Technology Transfer 31 (2006): 307–10. [Google Scholar] [CrossRef]
- Francine M. Deutsch. “Undoing gender.” Gender & Society 21 (2007): 106–27. [Google Scholar] [CrossRef]
- Shelley J. Correll. “Gender and the career choice process: The role of biased self-assessments.” American Journal of Sociology 106 (2001): 1691–730. [Google Scholar] [CrossRef]
- Shelley J. Correll. “Constraints into preferences: Gender, status, and emerging career aspirations.” American Sociological Review 69 (2004): 93–113. [Google Scholar] [CrossRef]
- Catherine Riegle-Crumb, Chelsea Moore, and Aida Ramos-Wada. “Who wants to have a career in science or math? Exploring adolescents’ future aspirations by gender and race/ethnicity.” Science Education 95 (2011): 458–76. [Google Scholar] [CrossRef]
- James D. Lee. “More than ability: Gender and personal relationships influence science and technology involvement.” Sociology of Education 75 (2002): 349–73. [Google Scholar] [CrossRef]
- Daniel Z. Grunspan, Sarah L. Eddy, Sara E. Brownell, Benjamin L. Wiggins, Alison J. Crowe, and Steven M. Goodreau. “Males under-estimate academic performance of their female peers in undergraduate biology classrooms.” PLoS ONE 11 (2016): e0148405. [Google Scholar] [CrossRef] [PubMed]
- Jonathan M. Kane, and Janet E. Mertz. “Debunking myths about gender and mathematics performance.” Notices of the American Mathematical Society 59 (2012): 10–21. [Google Scholar] [CrossRef]
- Daniel Voyer, and Susan D. Voyer. “Gender differences in scholastic achievement: A meta-analysis.” Psychological Bulletin 140 (2014): 1174–204. [Google Scholar] [CrossRef] [PubMed]
- Heidi B. Carlone. “The cultural production of science in reform-based physics: Girls’ access, participation, and resistance.” Journal of Research in Science Teaching 41 (2004): 392–414. [Google Scholar] [CrossRef]
- Susan Jones, and Debra Myhill. “‘Troublesome boys’ and ‘Compliant Girls’: Gender identity and perceptions of achievement and underachievement.” British Journal of Sociology of Education 25 (2004): 547–61. [Google Scholar] [CrossRef]
- Catherine Riegle-Crumb, Barbara King, Eric Grodsky, and Chandra Muller. “The more things change, the more they stay the same? Prior achievement fails to explain gender inequality in entry into STEM college majors over time.” American Educational Research Journal 49 (2012): 1048–73. [Google Scholar] [CrossRef] [PubMed]
- Heidi B. Carlone, Angela W. Webb, Louise Archer, and Mandy Taylor. “What kind of boy does science? A critical perspective on the science trajectories of four scientifically talented boys.” Science Education, 2015, 438–64. [Google Scholar] [CrossRef]
- Gayle A. Buck, Diandra Leslie-Pelecky, and Susan K. Kirby. “Bringing female scientists into the elementary classroom: Confronting the strength of elementary students’ stereotypical images of scientists.” Journal of Elementary Science Education 14 (2002): 1–8. [Google Scholar] [CrossRef]
- Bryan A. Brown. “Discursive identity: Assimilation into the culture of science and its implications for minority students.” Journal of Research in Science Teaching 41 (2004): 810–34. [Google Scholar] [CrossRef]
- Jessica J. Good, Julie A. Woodzicka, and Lylan C. Wingfield. “The effects of gender stereotypic and counter-stereotypic textbook images on science performance.” The Journal of Social Psychology 150 (2010): 132–47. [Google Scholar] [CrossRef] [PubMed]
- Ursula Kessels. “Fitting into the stereotype: How gender-stereotyped perceptions of prototypic peers relate to liking for school subjects.” European Journal of Psychology of Education 20 (2005): 309–23. [Google Scholar] [CrossRef]
- Margaret L. Signorella, Rebecca S. Bigler, and Lynn S. Liben. “Developmental differences in children’s gender schemata about others: A meta-analytic review.” Developmental Review 13 (1993): 147–83. [Google Scholar] [CrossRef]
- Lisa M. Pettitt. “Gender intensification of peer socialization during puberty.” New Directions for Child and Adolescent Development 2004 (2004): 23–34. [Google Scholar] [CrossRef] [PubMed]
- Nancy L. Galambos, David M. Almeida, and Almeida C. Petersen. “Masculinity, femininity, and sex role attitudes in early adolescence: Exploring gender intensification.” Child Development 61 (1990): 1905–14. [Google Scholar] [CrossRef] [PubMed]
- Louise Archer, Jennifer DeWitt, Jonathan Osborne, Justin Dillon, Beatrice Willis, and Billy Wong. “‘Not girly, not sexy, not glamorous’: Primary school girls’ and parents’ constructions of science aspirations.” Pedagogy, Culture & Society 21 (2013): 171–94. [Google Scholar] [CrossRef]
- Allison J. Gonsalves. “‘Physics and the girly girl—There is a contradiction somewhere’: Doctoral students’ positioning around discourses of gender and competence in physics.” Cultural Studies of Science Education 9 (2014): 503–21. [Google Scholar] [CrossRef]
- Sarah Banchefsky, Jacob Westfall, Bernadette Park, and Charles M. Judd. “But you don’t look like a scientist!: Women scientists with feminine appearance are deemed less likely to be scientists.” Sex Roles 75 (2016): 95–109. [Google Scholar] [CrossRef]
- Pamela R. Aschbacher, Erika Li, and Ellen J. Roth. “Is science me? High school students’ identities, participation and aspirations in science, engineering, and medicine.” Journal of Research in Science Teaching 47 (2010): 564–82. [Google Scholar] [CrossRef]
- Louise Archer, Jennifer DeWitt, Jonathan Osborne, Justin Dillon, Beatrice Willis, and Billy Wong. “‘Doing’ science versus ‘being’ a scientist: Examining 10/11-year-old schoolchildren’s constructions of science through the lens of identity.” Science Education 94 (2010): 617–39. [Google Scholar] [CrossRef]
- Louise Archer, Jennifer DeWitt, Jonathan Osborne, Justin Dillon, Beatrice Willis, and Billy Wong. “‘Balancing acts’: Elementary school girls’ negotiations of femininity, achievement, and science.” Science Education 96 (2012): 967–89. [Google Scholar] [CrossRef]
- Angela Calabrese Barton, Hosun Kang, Edna Tan, Tara B. O’Neill, Juanita Bautista-Guerra, and Caitlin Brecklin. “Crafting a future in science tracing middle school girls’ identity work over time and space.” American Educational Research Journal 50 (2013): 37–75. [Google Scholar] [CrossRef]
- Edna Tan, Angela Calabrese Barton, Hosun Kang, and Tara O’Neill. “Desiring a career in STEM-related fields: How middle school girls articulate and negotiate identities-in-practice in science.” Journal of Research in Science Teaching 50 (2013): 1143–79. [Google Scholar] [CrossRef]
- Tristan Bridges, and Cheri J. Pascoe. “Hybrid masculinities: New directions in the sociology of men and masculinities.” Social Compass 8 (2014): 246–58. [Google Scholar] [CrossRef]
- John H. Bishop, Matthew Bishop, Lara Gelbwasser, Shanna Green, Andrew Zuckerman, Amy Ellen Schwartz, and David F. Labaree. “Nerds and freaks: A theory of student culture and norms.” Brookings Papers on Education Policy 6 (2003): 141–213. [Google Scholar] [CrossRef]
- Sarah-Jane Leslie, Andrei Cimpian, Meredith Meyer, and Edward Freeland. “Expectations of brilliance underlie gender distributions across academic disciplines.” Science 347 (2015): 262–65. [Google Scholar] [CrossRef] [PubMed]
- Raewyn W. Connell, and James W. Messerschmidt. “Hegemonic masculinity rethinking the concept.” Gender & Society 19 (2005): 829–59. [Google Scholar] [CrossRef]
- Cheri Jo Pascoe. “‘Dude, You’re a Fag’: Adolescent masculinity and the fag discourse.” Sexualities 8 (2005): 329–46. [Google Scholar] [CrossRef]
- Campbell Leaper, and Christia S. Brown. “Perceived experiences with sexism among adolescent girls.” Child Development 79 (2008): 685–704. [Google Scholar] [CrossRef] [PubMed]
- Richard L. Luftig, and Marci L. Nichols. “An assessment of the social status and perceived personality and school traits of gifted students by non-gifted peers.” Roeper Review 13 (1991): 148–53. [Google Scholar] [CrossRef]
- Marion Händel, Wilma Vialle, and Albert Ziegler. “Student perceptions of high-achieving classmates.” High Ability Studies 24 (2013): 99–114. [Google Scholar] [CrossRef]
- Albert Ziegler, Marina Fidelman, Marold Reutlinger, Tanja Neubauer, and Michael Heilemann. “How desirable are gifted boys for girls, and gifted girls for boys?: Results of a chatroom study.” Australasian Journal of Gifted Education 19 (2010): 16–20. [Google Scholar]
- Deborah J. Laible, Gustavo Carlo, and Marcela Raffaelli. “The differential relations of parent and peer attachment to adolescent adjustment.” Journal of Youth and Adolescence 29 (2000): 45–59. [Google Scholar] [CrossRef]
- Constance Ellwood. “Questions of classroom identity: What can be learned from codeswitching in classroom peer group talk? ” The Modern Language Journal 92 (2008): 538–57. [Google Scholar] [CrossRef]
- Robert Crosnoe, Catherine Riegle-Crumb, Sam Field, Kenneth Frank, and Chandra Muller. “Peer group contexts of girls’ and boys’ academic experiences.” Child Development 79 (2008): 139–55. [Google Scholar] [CrossRef] [PubMed]
- Thomas D. Cook, Yingying Deng, and Emily Morgano. “Friendship influences during early adolescence: The special role of friends’ grade point average.” Journal of Research on Adolescence 17 (2007): 325–56. [Google Scholar] [CrossRef]
- Robert Crosnoe. “Friendships in childhood and adolescence: The life course and new directions.” Social Psychology Quarterly, 2000, 377–91. [Google Scholar]
- Rachael D. Robnett, and Campbell Leaper. “Friendship groups, personal motivation, and gender in relation to high school students’ STEM career interest.” Journal of Research on Adolescence 23 (2013): 652–64. [Google Scholar] [CrossRef]
- Peter M. Blau. Inequality and Heterogeneity: A Primitive Theory of Social Structure. New York: Free Press, 1977, vol. 7. [Google Scholar]
- Thomas J. Fararo, and John Skvoretz. “Unification research programs: Integrating two structural theories.” American Journal of Sociology 92 (1987): 1183–209. [Google Scholar] [CrossRef]
- Ted Mouw, and Barbara Entwisle. “Residential segregation and interracial friendship in schools.” American Journal of Sociology 112 (2006): 394–441. [Google Scholar] [CrossRef]
- Wendy Bottero, and Kenneth Prandy. “Social interaction distance and stratification.” The British Journal of Sociology 54 (2003): 177–97. [Google Scholar] [CrossRef] [PubMed]
- Jeffrey A. Smith, Miller McPherson, and Lynn Smith-Lovin. “Social distance in the United States Sex, Race, Religion, Age, and Education Homophily among Confidants, 1985 to 2004.” American Sociological Review 73 (2014): 432–56. [Google Scholar] [CrossRef]
- Steven M. Goodreau, Susan Cassels, Danuta Kasprzyk, Daniel E. Montaño, April Greek, and Martina Morris. “Concurrent partnerships, acute infection and HIV epidemic dynamics among young adults in Zimbabwe.” AIDS and Behavior 16 (2012): 312–22. [Google Scholar] [CrossRef] [PubMed]
- Donna Eder. School Talk: Gender and Adolescent Culture. New Brunswick: Rutgers University Press, 1995. [Google Scholar]
- Anthony G. Greenwald, Debbie E. McGhee, and Jordan L. K. Schwartz. “Measuring individual differences in implicit cognition: The implicit association test.” Journal of Personality and Social Psychology 74 (1998): 1464. [Google Scholar] [CrossRef] [PubMed]
- National Science Board. Science and Engineering Indicators 2016. Arlington: National Science Foundation, 2016. [Google Scholar]
- Jacob E. Cheadle, and Phillip Schwadel. “The ‘friendship dynamics of religion,’ or the ‘religious dynamics of friendship’? A social network analysis of adolescents who attend small schools.” Social Science Research 41 (2012): 1198–212. [Google Scholar] [CrossRef] [PubMed]
- Liesbeth Mercken, Christian Steglich, Philip Sinclair, Jo Holliday, and Laurence Moore. “A longitudinal social network analysis of peer influence, peer selection, and smoking behavior among adolescents in British schools.” Health Psychology 31 (2012): 450–59. [Google Scholar] [CrossRef] [PubMed]
- Andrea Knecht, Tom A. Snijders, Chris Baerveldt, Christian E. Steglich, and Werner Raub. “Friendship and delinquency: Selection and influence processes in early adolescence.” Social Development 19 (2010): 494–514. [Google Scholar] [CrossRef]
- Kaya de la Haye, Harold D. Green, David P. Kennedy, Michael S. Pollard, and Joan S. Tucker. “Selection and influence mechanisms associated with marijuana initiation and use in adolescent friendship networks.” Journal of Research on Adolescence 23 (2013): 474–86. [Google Scholar] [CrossRef] [PubMed]
- Robert Crosnoe. Fitting in, Standing out: Navigating the Social Challenges of High School to Get an Education. Cambridge: Cambridge University Press, 2011. [Google Scholar]
- Thomas A. DiPrete, and Claudi Buchmann. The Rise of Women: The Growing Gender Gap in Education and What It Means for American Schools: The Growing Gender Gap in Education and What It Means for American Schools. New York: Russell Sage Foundation, 2013. [Google Scholar]
- Sheri R. Levy, and Carol S. Dweck. “The impact of children’s static versus dynamic conceptions of people on stereotype formation.” Child Development 70 (1999): 1163–80. [Google Scholar] [CrossRef]
- Margaret E. Tankard, and Elizabeth L. Paluck. “Norm perception as a vehicle for social change.” Social Issues and Policy Review 10 (2016): 181–211. [Google Scholar] [CrossRef]
- Elizabeth Levy Paluck, Hana Shepherd, and Peter M. Aronow. “Changing climates of conflict: A social network experiment in 56 schools.” Proceedings of the National Academy of Sciences 113 (2016): 566–71. [Google Scholar] [CrossRef] [PubMed]
- Joscha Legewie, and Thomas A. DiPrete. “The high school environment and the gender gap in science and engineering.” Sociology of Education 87 (2014): 259–80. [Google Scholar] [CrossRef] [PubMed]
- Paula England. “The gender revolution uneven and stalled.” Gender & Society 24 (2010): 149–66. [Google Scholar] [CrossRef]
- Marilyn Fenichel, and Heidi Schweingruber. Surrounded by Science: Learning Science in Informal Environments. Washington: National Academies Press, 2010. [Google Scholar]
- Kathleen A. Fadigan, and Penny L. Hammrich. “A longitudinal study of the educational and career trajectories of female participants of an urban informal science education program.” Journal of Research in Science Teaching 41 (2004): 835–60. [Google Scholar] [CrossRef]
- Judy Diamond, Martin Powell, Angie Fox, Ann Downer-Hazell, and Charles Wood. World of Viruses. Lancaster: University of Nebraska Press, 2012. [Google Scholar]
- National Research Council. Identifying and Supporting Productive Programs in Out-of-School Settings. Washington: National Academy Press, 2015. [Google Scholar]
- Joan Williams. Unbending Gender: Why Family and Work Conflict and What To Do About It. New York: Oxford University Press, 2000. [Google Scholar]
- Yu-Sung Su, Andrew Gelman, Jennifer Hill, and Masanao Yajima. “Multiple imputation with diagnostics (mi) in R: Opening windows into the Black Box.” Journal of Statistical Software 45 (2011): 1–31. [Google Scholar] [CrossRef]
- Andrew Gelman, Gary King, and Chuanhai Liu. “Not asked and not answered: Multiple imputation for multiple surveys.” Journal of the American Statistical Association 93 (1999): 846–57. [Google Scholar] [CrossRef]
- Eugene Edgington. Randomization Tests, 3rd ed. NewYork: Marcel Dekker Inc., 1995, vol. 147. [Google Scholar]
- Anthony Kulesa, Martin Krzywinski, Paul Blainey, and Naomi Altman. “Sampling distributions and the bootstrap: The bootstrap can be used to assess uncertainty of sample estimates.” Nature Methods 12 (2015): 477–78. [Google Scholar] [CrossRef] [PubMed]
- Scott D. Gest, Alice J. Davidson, Kelly L. Rulison, James Moody, and Janet A. Welsh. “Features of groups and status hierarchies in girls’ and boys’ early adolescent peer networks.” New Directions for Child and Adolescent Development 118 (2007): 43–60. [Google Scholar] [CrossRef] [PubMed]
Boys (N = 212) | Girls (N = 232) | ||
---|---|---|---|
Race/Ethnicity | |||
White | 38% | 35% | |
Other than White | 62% | 65% | |
Grade | |||
6th grade | 29% | 32% | |
7th grade | 44% | 37% | |
8th grade | 29% | 31% | |
Parent attended college | |||
Yes | 66% | 64% | |
No | 18% | 24% | |
I don’t know | 16% | 12% | |
Boys–Girls 95% CI | |||
Self-assessed scientist potential | |||
I could become a scientist | 33% | 28% | [−4.06, 3.42] |
I might be able to become a scientist | 39% | 46% | [9.52, 5.33] |
I probably could not become a scientist | 10% | 11% | [−4.31, 6.86] |
I could not become a scientist | 9% | 7% | [−5.05, 5.01] |
I don’t know | 8% | 7% | [−8.69, 7.14] |
Science grades | |||
Mostly As | 23% | 27% | [−10.48, 3.17] |
Mostly As and Bs | 39% | 36% | [−4.62, 10.51] |
Mostly Bs | 5% | 5% | [−3.48, 3.48] |
Mostly Bs and Cs | 5% | 9% | [−7.63, −0.07] |
Mostly Cs | 4% | 2% | [−0.42, 4.62] |
Mostly below Cs | 2% | 2% | [−2.1, 2.48] |
A mix of As, Bs, and Cs | 21% | 19% | [−3.94, 8.59] |
Science career aspirations | |||
I want a job that: | |||
“uses a lot of science” | 14% | 8% | [1.02, 10.78] |
“uses some science” | 25% | 25% | [−6.76, 6.92] |
“uses a little science” | 19% | 23% | [−10.23, 2.4] |
“does not use any science” | 13% | 15% | [−6.83, 3.95] |
“I don’t know” | 29% | 29% | [−7.67, 6.63] |
I ________ Become a Scientist | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
“Could” | “Might be able to” | “Probably could not” | “Could not” | “I don’t know” | |||||||||||
Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | |
My grades in science class are: | |||||||||||||||
“Mostly As” | 46% | 2% | [−17, 20] | 42% | 1% | [−17, 19] | 4% | −4% | [−13, 5] | 4% | −1% | [−8, 7] | 4% | 2% | [−3, 9] |
“As and Bs” | 36% | 7% | [−7, 22] | 46% | −14% | [−29, 1] | 4% | 0% | [−6, 6] | 7% | 2% | [−5, 10] | 7% | 3% | [−3, 11] |
“Mostly Bs” | 27% | 10% | [−25, 46] | 27% | −6% | [−45, 34] | 27% | 19% | [−13, 51] | 0% | −25% | [−53, 0] | 18% | 1% | [−31, 35] |
“Bs and Cs” | 10% | −10% | [−35, 18] | 50% | 15% | [−24, 29] | 10% | −10% | [−35, 19] | 10% | 5% | [−13, 29] | 20% | 0% | [−31, 33] |
“Mostly Cs” | 0% | 0% | [0, 0] | 12% | −38% | [−100, 22] | 25% | 0% | [−67, 50] | 38% | 13% | [−57, 67] | 25% | 25% | [−57, 67] |
“Mostly below Cs” | 20% | 0% | [−59, 57] | 0% | 0% | [0, 0] | 20% | −20% | [−83, 50] | 0% | −40% | [−100, 0] | 60% | 60% | [0, 100] |
“Mixed” | 29% | 13% | [−4, 13] | 33% | −8% | [−28, 13] | 20% | −3% | [−20, 14] | 16% | 11% | [−1, 24] | 2% | −14% | [−26, −3] |
I Want a Job That Uses: | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
“A lot of science” | “Some science” | “A little science” | “Does not use any science” | “I don’t know” | |||||||||||
Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | Boys | Boys-Girls | 95% CI | |
I ________ become a scientist: | |||||||||||||||
“Could” | 28% | 14% | [1, 28] | 23% | −21% | [−36, −6] | 21% | 6% | [−7, 19] | 10% | 4% | [−5, 13] | 18% | −3% | [−16, 10] |
“Might be able to” | 7% | 0% | [−7, 7] | 30% | 5% | [−8, 18] | 23% | −3% | [−15, 9] | 8% | −1% | [−9, 8] | 31% | −0% | [−14, 13] |
“Probably could not” | 10% | 10% | [0, 25] | 33% | 26% | [2, 48] | 14% | −16% | [−40, 7] | 14% | −16% | [−40, 8] | 29% | −2% | [−30, 25] |
“Could not” | 0% | 0% | [0, 0] | 11% | 4% | [−15, 23] | 11% | −2% | [−24, 19] | 42% | 5% | [−29, 37] | 37% | −7% | [−41, 26] |
“I don’t know” | 6% | 0% | [−17, 16] | 22% | 22% | [5, 44] | 6% | −24% | [−50, 0] | 17% | −19% | [−48, 11] | 50% | 21% | [−13, 53] |
Gender of youth making assessment | Youth’s assessment of their friends | Focal Boy | Focal Girl | Focal Boy-Focal Girl | Boys–Girls 95% CI |
---|---|---|---|---|---|
Boys’ assessments of their boy and girl friends | The friend “is a science kind of person” | 28% | 27% | 1% | [−6%,6%] |
The friend “is not a science kind of person” | 46% | 57% | −11% | [−16%, −2%] | |
I don’t know | 26% | 17% | 9% | [3%, 14%] | |
100% | 100% | ||||
Total friendship ties | 1116 | 292 | |||
Focal Boy | Focal Girl | ||||
Girls’ assessments of their boy and girl friends | The friend “is a science kind of person” | 41% | 25% | 16% | [7%, 24%] |
The friend “is not a science kind of person” | 37% | 53% | −16% | [−23%, −6%] | |
I don’t know | 22% | 22% | 0% | [−9%, 7%] | |
100% | 100% | ||||
Total friendship ties | 206 | 1472 |
Boys | Girls | |
---|---|---|
Network Structure Indicators | ||
Edges (volume of ties) | −6.991 *** (0.165) | −6.498 *** (0.113) |
Mutual (both nominate) | 2.576 *** (0.133) | 2.882 *** (0.107) |
Weighted shared friends | 1.113 *** (0.062) | 1.046 *** (0.056) |
Demographic homophily measures | ||
Same race (base is different race) | 0.343 *** (0.055) | 0.221 *** (0.042) |
Same grade (base is different grade) | 2.462 *** (0.166) | 2.081 *** (0.116) |
Same grade in science class (base is different grades) | 0.204 *** (0.057) | 0.109 * (0.049) |
Same parental college attendance (base is different parental college status) | −0.042 (0.058) | 0.061 (0.044) |
Science career homophily (base is different career aspiration) | ||
Both youth want a career: | ||
that uses “A lot” of science | 0.327 * (0.153) | 0.480 * (0.196) |
that uses “Some” science | 0.225 * (0.096) | 0.033 (0.075) |
that uses “A little” science | 0.214 † (0.130) | 0.029 (0.092) |
that “Does not use any” science | 0.491 ** (0.145) | −0.071 (0.173) |
Both youth “Do not know” | 0.045 (0.093) | −0.018 (0.080) |
BIC | 5647 | 8136 |
Total number of students | 212 | 232 |
© 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gauthier, G.R.; Hill, P.W.; McQuillan, J.; Spiegel, A.N.; Diamond, J. The Potential Scientist’s Dilemma: How the Masculine Framing of Science Shapes Friendships and Science Job Aspirations. Soc. Sci. 2017, 6, 14. https://doi.org/10.3390/socsci6010014
Gauthier GR, Hill PW, McQuillan J, Spiegel AN, Diamond J. The Potential Scientist’s Dilemma: How the Masculine Framing of Science Shapes Friendships and Science Job Aspirations. Social Sciences. 2017; 6(1):14. https://doi.org/10.3390/socsci6010014
Chicago/Turabian StyleGauthier, G. Robin, Patricia Wonch Hill, Julia McQuillan, Amy N. Spiegel, and Judy Diamond. 2017. "The Potential Scientist’s Dilemma: How the Masculine Framing of Science Shapes Friendships and Science Job Aspirations" Social Sciences 6, no. 1: 14. https://doi.org/10.3390/socsci6010014
APA StyleGauthier, G. R., Hill, P. W., McQuillan, J., Spiegel, A. N., & Diamond, J. (2017). The Potential Scientist’s Dilemma: How the Masculine Framing of Science Shapes Friendships and Science Job Aspirations. Social Sciences, 6(1), 14. https://doi.org/10.3390/socsci6010014