Rabota.uz, Headhunters, and Uzjobs.<sup>4</sup> In preparation for the experiment, we collected recruitment ads listed on each for the most demanded six occupations. We cross-checked this list to exclude duplications across the four job portals (such that each employer received an application from only a single fictitious applicant), though in practice the number of duplications among job portals was small.

For recording callbacks, we used the “Backup and Restore” function to recall the full call log history for each of the phone numbers created for the study. We then counted all callbacks and emails received from the target firms. The submission process proceeded in two phases. For the positions of accountant, office manager, and IT specialist, applications were completed in February 2020. In May 2020, the team stopped the study given the large decline in the number of open positions during the nationwide lockdown due to the outbreak of COVID-19, and the atypical situation during this time. The study resumed in November 2020 with a focus on the positions of welder, call center operator, and driver, when the situation with COVID-19 in the country began improving. The experiment ended in early February 2021.

We expected that gender bias would vary by occupations typically considered male or femaledominated. The first cohort included office manager (secretary), accountant, and IT specialist positions. We expected that office manager and accountant positions were female dominated occupations, and IT specialist a male dominated occupation. We applied to 294 open jobs by the end of February 2020. The second phase began in November 2020 and included applications to 477 announcements. The second group of occupations included welder, driver, and call center operator. We expected that welder and driver were male-dominated positions while call-center operator was a female dominated position. The total number of applications reached 771 across the two study phases. We received 390 callbacks in total, and approximately 245 job interview invitations in response to these submissions.<sup>5</sup> The standard method (used for instance in Booth and Leigh (2010), Zhou et al. (2013), Kaas and Manger (2012), Asali et al (2018), Zhang et al. (2021)) tests the difference in the callback rate attributable to the randomly assigned gender in each application in a simple regression framework. We use probit model as the dependent variable is binary (when the dependent variable Y event is observed, it takes the value 1 otherwise 0). The simplest binary selection model is the linear probability model, in which the probability of occurrence, p, is defined as a linear function dependent on the explanatory variable(s) (Stock and Watson, 2007): This provides a summary of differences in response across all observations in the study (not yet stratified by profession) where φ shows cumulative standardized normal distribution function. For comparison and robustness, we also estimate a probit model in the same spirit, taking the form: _Response(0,1)= +β_ 1 _JobType+β_ 2 _Female+β_ 3 _(JobType×Female)+ε_ (2) αα

> 4 In addition, there is one state-owned job portal – ishmehnat.uz – which is managed by the Ministry of Employment and Labor Relations in Uzbekistan. We excluded ishmehnat.uz from the study because the site has a user base that is comparatively quite small, and it also requires official registration of employment status and provision of personal details of applicants (passport number, taxpayers’ number, and other details).

> 5 After accounting for duplications .

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