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Abstract
Gender discrimination is present across various fields, but identifying the underlying mechanism is challenging. We demonstrate own-gender favouritism in a field setting that allows for clean identification of tastes versus beliefs: the One Bid game on the TV show The Price Is Right. Players must guess an item's value without exceeding it, leaving the last bidder with a dominant 'cutoff' strategy of overbidding another player by ${\$}$1. We show that last bidders are significantly more likely to cut off opposite-gender opponents. This behaviour is explained by own-gender favouritism rather than beliefs that cutting off opposite-gender opponents is more profitable.

We investigate optimal group member configurations for producing a maximally accurate group forecast. Our approach accounts for group members that may be biased in their forecasts and/or have errors that correlate with the criterion values being forecast. We show that for large forecasting groups, the diversity of individual forecasts linearly trades off with forecaster accuracy when determining optimal group composition.

During an Ebola virus disease (EVD) outbreak, calculating the exposure window of a confirmed case can assist field investigators in identifying the source of infection and establishing chains of transmission. However, field investigators often have difficulty calculating this window. We developed a bilingual (English/French), smartphone-based field application to assist field investigators in determining the exposure window of an EVD case. The calculator only requires the reported date of symptoms onset and the type of symptoms present at onset or the date of death. Prior to the release of this application, there was no similar electronic capability to enable consistent calculation of EVD exposure windows for field investigators. The Democratic Republic of the Congo Ministry of Health endorsed the application and incorporated it into trainings for field staff. Available for Apple and Android devices, the calculator continues to be downloaded even as the eastern DRC outbreak resolved. We rapidly developed and implemented a smartphone application to estimate the exposure window for EVD cases in an outbreak setting