Working Papers and Work in Progress

Papers under review and working papers listed by date of release in descending order:

Khan, Nuzaina, Rand, David, and Olga Shurchkov. “He Said, She Said: Who Gets Believed When Spreading (Mis)information”  (Last revised April 2024) NEW DRAFT! COMMENTS WELCOME!

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Abbreviated Instructions, Debriefing and Full List of Posts


Complete Bank of Stock Photos Used for Profile Images


Online SI Appendix

ABSTRACT

We design an online experiment that mimics a Twitter/X “feed” to test whether (perceived) poster gender influences users’ propensity to doubt the veracity of a given post. On average, posts by women are less likely to be flagged as concerning than identical posts by men. Heterogeneity analysis reveals that men are more likely to flag female-authored posts as the post’s topic domain becomes more male-stereotyped.  Female users do not exhibit the same bias.  Actual post veracity, user ideology, and user familiarity with Twitter do not explain the findings. Flagging behavior on Twitter’s crowdsourced fact-checking program is consistent with these findings.


KEY WORDS

Gender differences, misinformation, economic experiments

Flory, Jeff, Leibbrandt, Andreas, Shurchkov, Olga, Stoddard, Olga, and Alva Taylor. Consumer Preferences for Diversity: A Field Experiment in Product Design,” Working Paper (Last revised January 2023)

Online Appendix

ABSTRACT

This paper describes a randomized controlled field experiment designed to measure how individuals respond to racial and gender diversity in representations of certain archetypical occupations. We ask participants in two pools – a tech conferences and online – to evaluate their user experience with an image search engine tool and randomize them to see either diverse or non-diverse images. Subjects in the less diverse treatment view images that are predominantly white men for the high-status occupations (boss and professor) and predominantly women for the low-status occupations (nurse and clerk). In the more diverse treatment, subjects view image sets that contain a more equitable distribution of gender and race. We observe that diverse images result in significantly higher ratings across all participants and find no evidence of in-group bias in this context. However, women are disproportionately more dissatisfied with the lack of diversity in high-status occupations (boss and professor) than men are. For the low-status words (clerk and nurse), we find weaker treatment effects and no heterogeneity in the satisfaction ratings by gender or race. Free response qualitative data provide a potential explanation for the findings: while the extreme underrepresentation of women and minorities in the high-status, low-pay professions is salient, the equivalent underrepresentation of white men in the low-status, low-pay professions is less salient. Correcting the asymmetry in the way we promote diversity in high-status and low-status domains has important policy implications.


KEYWORDS

Diversity; Gender differences; Economic experiments 


CITATION

Flory, Jeffrey, Leibbrandt, Andreas, Shurchkov, Olga, Stoddard, Olga, and Alva Taylor. 2023. Consumer Preferences for Diversity: A Field Experiment in Product Design. Working Paper. Available at SSRN: https://ssrn.com/abstract=4281634.

Work in progress

Alston, Mackenzie, Deryugina, Tatyana, and Olga Shurchkov. “The Role of Social Media in Academic Careers

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