The influence of the applicants’ gender on the modeling of a peer review process by using latent Markov models
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In the grant peer review process we can distinguish various evaluation stages in which assessors judge applications on a rating scale. Bornmann & al.  show that latent Markov models offer a fundamentally good opportunity to model statistically peer review processes. The main objective of this short communication is to test the influence of the applicants’ gender on the modeling of a peer review process by using latent Markov models. We found differences in transition probabilities from one stage to the other for applications for a doctoral fellowship submitted by male and female applicants.
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