Only quality counts! Naomi Ellemers DEWIS symposium, February 2016

Transcription

1 Only quality counts! Naomi Ellemers DEWIS symposium, February 2016

2 Quality through diversity Business Case Gendered innovations Fund raising Horizon 2020 research teams, evaluation panels, research questions

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7 WHAT IS THE PROBLEM?

8 I don t believe there is a glass ceiling We only look at quality Women are not interested I don t believe we have anything against women Our director is a woman, so it is possible! We just appointed another woman 8

9 You can examine this!

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11 Men Women UD UHD HGL

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17 IS THIS JUST ABOUT QUALITY?

18 Blatant Traditional, direct They are less able Exclusion by others Subtle Modern, indirect Different qualities, values Personal choices

19 Denial of discrimination Double message: If women have equal opportunities, and women are less successful,...this must be due to their own competence, ambition, or priorities!

20 ERC Starting and Advanced Grants

21 Grants awarded at NWO 30% 25% 20% 15% 10% Men Women 5% 0%

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23 Lowest Scales Highest Scales

24 Differences M/F : Salary scientists Salary support staff Tenured positions Parttime / Teaching appointments Chairs / Management positions

25 THE LARRY SUMMERS QUESTION

26 Jan. 17, 2005 CAMBRIDGE -- The president of Harvard University, Lawrence H. Summers, sparked an uproar at an academic conference Friday when he said that innate differences between men and women might be one reason fewer women succeed in science and math careers. Summers also questioned how much of a role discrimination plays in the dearth of female professors in science and engineering.

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28 Review ofmeta-analyses Cognitive performance Personality and social behavior Psychological well-being e.g. math (343 studies) e.g. leadership e.g. (academic) self-esteem Overall, based on numerous meta-analyses reported here, there is much evidence in support of the gender similarities hypothesis. Gender differences are small or trivial. Mountains of research have been conducted on psychological gender differences, yielding the patterns of results described above. This review reveals much evidence of the importance of context in creating or erasing gender differences. 28

29 Innate differences? Neil de Grasse Tyson, Astrophysicist I ve never been female, but I ve been black all my life. As a 9 year old, he visited the Hayden Planetarium, and decided he wanted to become an astrophysicist. This led him to the path of greatest resistance. His teachers asked him, time and again: Don t you want to become an athlete?

30 Economist Donald / Deirdre McCloskey I've just started to get the treatment that women get. When I was the sole woman in a group of a half-dozen economists and I made a point no one took notice. A few minutes later George made the same point and the men said, "That's a great point, George!"

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32 IMPLICIT EXPECTATIONS

33 Perpetrator (M/F) Implicit expectations Victim Tension, insecurity Interaction Cycle of motivation and performance loss 33

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36 Implicit associations Men Women Men Women - professional career - family - hard sciences - humanities/social sciences

37 Creativity is associated with masculinity Proudfoot et al., 2015, Psychological Science Women are seen as less talented Leslie et al., Science, 347, Gender bias in language use undermines selection of women Gaucher et al., JPSP, 101,

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39 My professor is a genius

40 WHY IS THIS IMPORTANT?

41 Asessing talent In the top of the distribution: No differences M / F in publications of citations Objective differences are no longer distinctive Criteria are vague and ambiguous What is decisive? Coincidence, context, group dynamics Van Arensbergen (2014) Rathenau Instituut

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44 NWO Annual Report 2014 CV s 10 years after VENI ( , N=262; publications, citations, position): Veni does not predict productivity, but does predict career success After controlling for productivity etc. : Gender predicts career success Van den Besselaar & Sandström, JOI, 2015

45 Women have lower returns from scholarly achievements Management Professors Tier 1 Institutions CV data (N=511; 90% van populatie) 50% 40% Vrouwen hebben minder kans op endowed chair, na correctie voor : productiviteit (publicaties, citaties) Achtergrondvariabelen (jaren na PhD, vakgebied) Persoonlijke omstandigheden (kinderen in huis) 30% 20% 10% 0% Mannen Vrouwen Treviño et al., JOM, 2015

46 552 Economists In top-30 US institutions 5-7 years after PhD 422 Male 130 Female No difference in: Number of papers Single authored Co-authored After controlling for Journal impact Citations Co-author seniority 100% 80% 60% 40% 20% 0% Tenure Men Women

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48 WHAT CAN YOU DO?

49 The illusion of equal opportunities makes people less alert Implicit mechanisms difficult to control Denial of discrimination part of the problem 49

50 Beyond common sense Good intentions are not enough Implicit discrimination is most damaging Just adding a few women does not help 50

51 What then? Focus on facts, don t rely on your feelings Keep statistics to set goals and monitor progress Acknowledge that nobody is objective Correct for unintended bias training, procedures, criteria, monitoring 51

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53 THANK YOU