A Public Dataset of Firm-Level Employment Practices

Awarded Scholars:
Peter Norlander, Loyola University, Chicago
Project Date:
Jul 2022
Award Amount:

Corporate human resource practices, such as work-from-home policies, shape the future of work, however, researchers do not have a reliable, long-term, public dataset on firm-level practices. Labor scholar Peter Norlander will develop a dataset of employment practices for a sample of publicly traded firms and a sample of large private firms, government agencies, and non-profit employers. He will complete the construction of machine learning algorithms that will identify job characteristics using the text from job advertisements.


RSF: The Russell Sage Foundation Journal of the Social Sciences is a peer-reviewed, open-access journal of original empirical research articles by both established and emerging scholars.


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