Mesurer les risques psychosociaux : de la commensuration au compromis

doi:10.4121/3500c5c4-e22c-4f39-8a01-9f95bfa96b02.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/3500c5c4-e22c-4f39-8a01-9f95bfa96b02
Datacite citation style:
Beau, Pauline; Jerman, Lambert (2025): Mesurer les risques psychosociaux : de la commensuration au compromis. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/3500c5c4-e22c-4f39-8a01-9f95bfa96b02.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

In this article, we look at the measurement of the social and how a quantified representation of psychosocial risks can be accepted in organizations. Based on interviews and documentation from two major international companies, we study the construction of psychosocial risk measures using a benchmark occupational health questionnaire. We show that the measurement of psychosocial risks can be a compromise in the two organizations studied, when it succeeds in evacuating the very situations experienced at work that it sets out to represent. Our results show how this compromise results from a set of practices and discourses by which individuals (1) tinker with and (2) extrapolate the measures produced from the questionnaire, to the point of (3) neantizing psychosocial risks through their representation in these two organizations. In this way, our study hopes to contribute to research into the difficulty of taking social issues into account in accounting, as well as to work dedicated to the commensuration of these risks, whose manifestations are difficult to represent in organizations.

history
  • 2025-01-14 first online, published, posted
publisher
4TU.ResearchData
organizations
Toulouse Business School, Department of Accounting.

DATA - not available

We have contractually agreed with our respondents to maintain their anonymity throughout data collection, analysis and dissemination.

DATA