Pink queue and Double Standard: what Markov Chains uncover in academic career progressions

This study is the first modeling academic career progression using multi-state models, an approach that allows to compute additional quantities of interest never produced in this context, such as the probability of attaining specific academic positions over given time horizons and the average time required to reach them. Potential gender differences along these dimensions are assessed by comparing these metrics computed for male and female scholars separately, while accounting for productivity, individual preferences, and even seniority, which are often cited as explanations for women’s disadvantage in academic careers. Leveraging a suitably-built highly informative dataset covering the universe of professors having worked in Italian universities between 2016 and 2021, we show a gap in the probabilities of career advancement that reduces with the career horizon but never vanishes, stabilizing around 2 (3) percentage points for those starting their career as assistant (associate) professors. In addition, we find that female scholars require up to two additional years to reach the highest academic rank (full professorship) compared with otherwise equivalent male counterparts, a phenomenon we label the “pink queue”. Finally, we find a systematic misalignment in career advancement probabilities between male and female scholars with comparable productivity, whereby women achieve the same advancement chances as men only when they attain higher productivity levels, suggesting the presence of a potential “double standard”.