"How to Ensure the Replicability of an Ad Hoc Research Strategy: A Few Lessons Drawn from the Sociology of the Concept of Public Service"

Thursday, 19 July 2018: 09:42
Oral Presentation
This contribution investigates the methodological issue raised by my doctoral research on the exponents of public service under the French Third Republic. My survey rested upon a specific kind of prosopographical enquiry (n = 116), based on a concept rather than on just being a member of a given institution. It was not about studying a “grand corps” (the “Conseil d’État”), a professional group (legal academics) nor a discipline (administrative law), it was about taking an idea (“public service”) in its historical formation as a starting point. The attribute “being an exponent of public service” is not as objectively given than an event (such as “being deported in a camp”) or a membership in an institution (such as “being a MP”). In other words, one cannot find a list of public-service thinkers in any historical sources. Therefore, the point of the research was to define indicators that could operationalise individuals who significantly used the syntagm “public service”.

This presentation will account for the replicability of a constructionist method that can be deemed unusual. Namely, set theory, used to compare the studied population with a control group, proved particularly appropriate for a “sample” that was not meant to be representative since it had not been randomly drawn from a population, but rather constituted by the weight that each actor exerted in the studied field. Also, in such a varied corpus comprising “conseillers d’État”, academics, politicians and trade unionists, it proved impossible to compare the sample of “conseillers d’État” with the thousands of members of this institution under the Third Republic while, at the same time, doing the same for all other groups, given the countless number of public servants in this 70 year period. Instead, we used other techniques (archival ethnography, geometric data analysis) to devise an unbiased “sample”.