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Building a prosopographical database through coding. Issues and benefits of automating data collection in human and social sciences

Authors: Bina, Nicolas; Gramaize, Léopold;

Building a prosopographical database through coding. Issues and benefits of automating data collection in human and social sciences

Abstract

L’accessibilité croissante des ressources numérisées permet d’envisager de nouveaux moyens de production de la recherche en sciences humaines et sociales. A partir d’une recherche prosopographique de science politique portant sur les directeurs et directrices d’administrations centrales, qui occupent les postes de direction des ministères, cet article retrace les travaux qui ont débouché sur l’écriture d’un code informatique constitutif d'une base de données de plus de 140 000 entrées à partir de données publiques (via le Journal officiel ) et privées (via la presse spécialisée). Ce corpus inédit de données résulte du préalable rassemblement de l’information depuis un nombre fini de sources et constitue une mine d’information quasi- exhaustive sur les profils et parcours d’une élite de la fonction publique d’Etat, abondant les travaux de sociologie et de science politique sur les alternances, les structures de l’administration et leur évolution. Au moyen de savoir-faire techniques, de précautions et d’étapes successives détaillées dans cet article, le processus de codage informatique et ses ressources apparaissent comme un puissant vecteur de renouvellement des pratiques prosopographiques en sciences humaines et sociales. En effet, la disponibilité croissante de données et de ressources numérisées permet d'élargir les champs de recherches tout en augmentant considérablement la masse d'informations qu’il est possible de traiter. Les travaux conduits par les deux auteurs identifient de solides points de convergence méthodologiques, ouvrant de larges horizons communs pour la programmation informatique et les sciences humaines et sociales.

The increasing availability of digitised resources opens up new ways of producing research in human and social sciences. Based on prosopographical research in political science into the littlestudied directors of central government departments, who hold executive positions in the ministries, this article outlines the exchanges between the authors, which led to the writing of a computer code that made it possible to set up a database with over 140,000 items based on public (via the Journal officiel) and private data (via a specialised publication). This unprecedented corpus of data results from the prior collation of information from a limited number of sources and constitutes an almost exhaustive source of information on the profiles and career paths of an elite of the senior civil service of the French State, making it possible to feed sociological and political science studies on changes of government, administrative structures and their evolution. By using the technical know-how, precautions and successive stages outlined in this article, the computer coding process and its resources appear to be a powerful vector for renewing prosopographical practices in human and social sciences. Indeed, the growing availability of digitised data and resources makes it possible to broaden the fields of research while considerably increasing the mass of information that can be processed. The work of both authors highlights solid methodological overlaps, opening up broad common horizons for computer programming and human and social sciences.

Keywords

prosopography, fonction publique, IA générative, elite studies, senior civil servants, code informatique, generative AI, élites, quantitative methods, computer code, méthodes quantitatives, prosopographie, [SHS.SCIPO] Humanities and Social Sciences/Political science, Python

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average