> Here is the most glaring problem with this analysis: It cobbles together a dataset of “professional profiles” which lack the two of the most central datapoints to studying the gender pay gap issue:
> Actual GENDER of the individuals whose profiles are being analyzed
> Actual PAY (compensation) for those same individuals
> To compensate for the missing data, the team uses a machine-learning model to infer gender; and attempts to join the de-identified “professional profiles” to salary data from the US Bureau of Labor Statistics… which is impossible to do at the individual level.
Well, it is, as someone said (from my aging memory): "Mckinsey is to middle class, what flesh eating bacteria is to human skin".
P.S. Why it is so difficult to select something on Android ?
