Gender, beauty and support networks in academia: evidence from a field experiment

Magdalena Smyk, Michał Krawczyk

The Choice Lab, Bergen

March 17, 2016

GendEqU project is sponsored by EEA/Norway Grants

Group for Research in Applied Economics

2

Broad motivation

Huge gender gap at higher academic positions…

This is partly due to gender differences in academic productivity…

…which tends to be difficult to explain in terms of abilities or preferences

3

Support networks in the academia

Participation in social networks increase probability of receiving job offer (McDonald, 2011) and scientific productivity (Reagans and Zuckerman, 2001).

Colussi (2015): editor’s former PhD students and faculty colleagues improve their publication outcomes

Balliet et al. (2001) meta analysis: more cooperation in male-male interactions

Differences in experience between women and men:

Mentoring (Chandler, 1996)

Possibly collaboration (Gersick et al. 2000) (although Long (1992) Van Rijnsoever et al. (2008) found no differences and McDowell et al. (2006) only in historical data. ). Note: Ynalvez and Schrumb (2011) claim that networks matter NOT via formal collaborative projects.

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Can we blame the ``old-boys network”?

Are (male) scholars more willing to ``lend a hand’’

to a male researcher than a female?

Study 1 (data request)

• 247 papers (recent EE, JEBO, GEB papers reporting experiments that meet certain criteria)

• Ask for raw data from their experiments

• E-mails from two accounts: – Female student

– Male student

• Randomly chosen samples of subjects: – equal distribution of male and female subjects

– three geographical regions (Europe, Australia and Asia, Americas).

• A reminder after three weeks

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Study 1 – measures of success

Response rate = number of responses we received/

number of e-mails sent (successfully)

Compliance rate = number of datasets we

received/number of e-mails sent

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Study 1 (data request): RESULTS

Female Student Male Student

No. of requests 100 105

Response rate 75% 74.3%

MWW test (p-value) 0.91

Marginal effects* -0.01 (insignificant)

Compliance rate 34% 35.2%

MWW test (p-value) 0.85

Marginal effects* -0.02 (insignificant)

Notes: *probit regression; gender, university region, fixed effects of journal, date of sending the request and number of datasets we asked for.

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Study 2

Extension:

10 fields of study: psychology, sociology, economics, mathematics, law, computer science, philosophy, medicine, physics and chemistry

two types of request (much smaller):

Article treatment – we ask for full text of subject’s paper

Meeting treatment – we ask for a meeting during office hours or Skype/phone call to discuss possible mentoring for graduate studies

additional dimension: physical attractiveness

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Physical attractiveness

Pre-study: Pictures with the highest and the lowest average rank were chosen.

Gmail picture + website link

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Sampling for Study 2

One hundred top faculties from QS World University Rankings

Four (randomly chosen) scholars from each faculty

Faculties without websites or without list of employees – excluded

Article Treatment – 1287 scholars (discarding those with no known papers in English)

Meeting Treatment – 1488 scholars

No gender balance in the sample (male majority)

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Study 2: dependant variables

Response rate = number of responses we received/

number of e-mails sent (successfully)

Article Treatment:

Compliance rate = number of full texts we

received/ number of e-mails sent

Meeting Treatment:

Compliance rate = number of meetings

scheduled or offered/ number of e-mails sent

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Study 2: results (Article Treatment)

Attractive

Female

Less

Attractive

Female

Attractive

Male

Less

Attractive

Male

No. of requests 343 307 337 300

Response rate 56.6% 67.1% 63.2% 62.4%

MWW test p-value

(vs. attractive female) 0.006 0.08 0.08

(vs. less attractive female) 0.3 0.33

(vs. attractive male) 0.97

Compliance rate 49% 60% 56.7% 54.8%

MWW test p-value

(vs. attractive female) 0.005 0.04 0.2

(vs. unattractive female) 0.4 0.14

(vs. attractive male) 0.5

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Study 2: results (Meeting Treatment)

Attractive

Female

Less

Attractive

Female

Attractive

Male

Less

Attractive

Male

No. of requests 370 378 374 366

Response rate 45.7% 47.6% 43.9% 44.3%

MWW test p-value

(vs. attractive female) 0.59 0.62 0.7

(vs. less attractive female) 0.3 0.36

(vs. attractive male) 0.91

Compliance rate 29.2% 34.4% 27% 27.6%

MWW test p-value

(vs. attractive female) 0.13 0.51 0.63

(vs. unattractive female) 0.03 0.05

(vs. attractive male) 0.86

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Study 2: results (probit)

Article

treatment

(1)

Article

treatment

(2)

Meeting

treatment

(1)

Meeting

treatment

(2)

response compliance response compliance

attractive female -0.08* -0.11*** 0.02 0.02

less attractive female 0.03 0.18 0.05 0.09***

less attractive male -0.02 -0.06 -0.005 0.001

female scholar -0.05 -0.07** -0.09*** -0.09***

Observations 1287 1287 1488 1488

Notes: Marginal effects from probit regressions; reference category is attractive male; regressions include subjects’ characteristics (gender, university region, university ranking position, field of study), date of sending the request and year of the paper publication (in Article treatment); *** p<0.01, ** p<0.05, * p<0.1.

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Robustness check and additional dimensions

No interaction of genders

Stronger results (higher marginal effect) in the subsample of subjects who has G-Talk option available

Lack of field-specific effects

Nr of unique vistors on websites = 44% of the nr of subjects

Attractive senders websites more popular by 10 pp on average

Refusals in the Meeting Treatment:

55/124 (males) to 34/111 (females) negative e-mail with explanation why someone cannot meet the reqeustor

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Conclusions

GOOD NEWS!

No gender bias in responding to or fullfilling requests

This result seems robust across fields and treatments

BUT…

Attractivness can play a role – but only in the case of female students

There seems to be an interaction with treatment

Cautios interpretation: female students considered less competent but more likable

Thank you for your attention! Authors: Magdalena Smyk, Michał Krawczyk e-mail: mkrawczyk@wne.uw.edu.pl

More about our research on

http://grape.uw.edu.pl

Twitter: @GrapeUW