Literature DB >> 29941572

How gender determines the way we speak about professionals.

Stav Atir1, Melissa J Ferguson2.   

Abstract

Gender inequality persists in many professions, particularly in high-status fields, such as science, technology, engineering, and math. We report evidence of a form of gender bias that may contribute to this state: gender influences the way that people speak about professionals. When discussing professionals or their work, it is common to refer to them by surname alone (e.g., "Darwin developed the theory of evolution"). We present evidence that people are more likely to refer to male than female professionals in this way. This gender bias emerges in archival data across domains; students reviewing professors online and pundits discussing politicians on the radio are more likely to use surname when speaking about a man (vs. a woman). Participants' self-reported references also indicate a preference for using surname when speaking about male (vs. female) scientists, authors, and others. Finally, experimental evidence provides convergent evidence: participants writing about a fictional male scientist are more likely to refer to him by surname than participants writing about an otherwise identical female scientist. We find that, on average, people are over twice as likely to refer to male professionals by surname than female professionals. Critically, we identified consequences of this gender bias in speaking about professionals. Researchers referred to by surname are judged as more famous and eminent. They are consequently seen as higher status and more deserving of eminence-related benefits and awards. For instance, scientists referred to by surname were seen as 14% more deserving of a National Science Foundation career award.

Entities:  

Keywords:  evaluation; gender; gender bias; judgment; reference

Mesh:

Year:  2018        PMID: 29941572      PMCID: PMC6048538          DOI: 10.1073/pnas.1805284115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  8 in total

1.  National differences in gender-science stereotypes predict national sex differences in science and math achievement.

Authors:  Brian A Nosek; Frederick L Smyth; N Sriram; Nicole M Lindner; Thierry Devos; Alfonso Ayala; Yoav Bar-Anan; Robin Bergh; Huajian Cai; Karen Gonsalkorale; Selin Kesebir; Norbert Maliszewski; Félix Neto; Eero Olli; Jaihyun Park; Konrad Schnabel; Kimihiro Shiomura; Bogdan Tudor Tulbure; Reinout W Wiers; Mónika Somogyi; Nazar Akrami; Bo Ekehammar; Michelangelo Vianello; Mahzarin R Banaji; Anthony G Greenwald
Journal:  Proc Natl Acad Sci U S A       Date:  2009-06-22       Impact factor: 11.205

2.  Expectations of brilliance underlie gender distributions across academic disciplines.

Authors:  Sarah-Jane Leslie; Andrei Cimpian; Meredith Meyer; Edward Freeland
Journal:  Science       Date:  2015-01-16       Impact factor: 47.728

3.  Our obsession with eminence warps research.

Authors:  Simine Vazire
Journal:  Nature       Date:  2017-07-04       Impact factor: 49.962

4.  The Matthew effect in science funding.

Authors:  Thijs Bol; Mathijs de Vaan; Arnout van de Rijt
Journal:  Proc Natl Acad Sci U S A       Date:  2018-04-23       Impact factor: 11.205

5.  Speaker Introductions at Internal Medicine Grand Rounds: Forms of Address Reveal Gender Bias.

Authors:  Julia A Files; Anita P Mayer; Marcia G Ko; Patricia Friedrich; Marjorie Jenkins; Michael J Bryan; Suneela Vegunta; Christopher M Wittich; Melissa A Lyle; Ryan Melikian; Trevor Duston; Yu-Hui H Chang; Sharonne N Hayes
Journal:  J Womens Health (Larchmt)       Date:  2017-02-16       Impact factor: 2.681

6.  Science faculty's subtle gender biases favor male students.

Authors:  Corinne A Moss-Racusin; John F Dovidio; Victoria L Brescoll; Mark J Graham; Jo Handelsman
Journal:  Proc Natl Acad Sci U S A       Date:  2012-09-17       Impact factor: 11.205

7.  Gender gaps: who needs to be explained?

Authors:  D T Miller; B Taylor; M L Buck
Journal:  J Pers Soc Psychol       Date:  1991-07

8.  Reviewer bias in single- versus double-blind peer review.

Authors:  Andrew Tomkins; Min Zhang; William D Heavlin
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-14       Impact factor: 11.205

  8 in total
  6 in total

1.  Speaking of gender bias.

Authors:  May R Berenbaum
Journal:  Proc Natl Acad Sci U S A       Date:  2019-04-09       Impact factor: 11.205

2.  Gender inequities in the online dissemination of scholars' work.

Authors:  Orsolya Vásárhelyi; Igor Zakhlebin; Staša Milojević; Emőke-Ágnes Horvát
Journal:  Proc Natl Acad Sci U S A       Date:  2021-09-28       Impact factor: 11.205

3.  Inequity and Women Physicians: Time to Change Millennia of Societal Beliefs.

Authors:  Connie Newman; Kim Templeton; Eliza Lo Chin
Journal:  Perm J       Date:  2020-09

4.  In some professions, women have become well represented, yet gender bias persists-Perpetuated by those who think it is not happening.

Authors:  C T Begeny; M K Ryan; C A Moss-Racusin; G Ravetz
Journal:  Sci Adv       Date:  2020-06-26       Impact factor: 14.136

5.  Words, images and gender: Lessons from a survey on the public perception of synthetic biology and related disciplines.

Authors:  Manuel Porcar; Adriel Latorre-Pérez; Esther Molina-Menor; Martí Domínguez
Journal:  EMBO Rep       Date:  2019-06-26       Impact factor: 8.807

6.  Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections.

Authors:  Titus von der Malsburg; Till Poppels; Roger P Levy
Journal:  Psychol Sci       Date:  2020-01-08
  6 in total

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