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Record W4367158898 · doi:10.7202/1080933ar

Social Status of Researchers And Professional Practices in the Field of Research Aimed at Social Intervention in France

2021· article· en· W4367158898 on OpenAlexaff
Marc‐Adélard Tremblay

Bibliographic record

VenueCulture · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicInnovative Education Methods and Tools
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLegitimacyField (mathematics)PoliticsPublic relationsPolitical scienceSocial researchSociologyIntervention (counseling)Social sciencePublic administrationLawPsychology

Abstract

fetched live from OpenAlex

During a governmental mission to France in March of 1988 the author evaluated the effects of the status and professional practices of researchers on their work in the field of ‘social research’. This type of research is largely financed by sectorial ministeries and private associations formed under the provisions of the law of 1901. I examined the sociopolitical and scientific milieu of knowledge production in this field of study. Such research on social aspects of health, social problems and income security raises fundemental epistemological questions regarding its legitimacy, specificity, scientific validity, and applicability. A traditional theoretical orientation in social science research, lack of interest in funding this type of research at the CNRS (Centre National de la Recherche scientifique) and scientific ministries, and the precarious status of young researchers all characterize this new field of study and also constrain its development. However a new momentum is under way, due to recent initiatives by the Mission de Recherche et d’Experimentation (MIRE), the Ministère des affaires sociales et de l’emploi, and to political lobbying by public bodies and private organizations with the goal of revitalizing social research aimed at finding concrete and innovative solutions to contemporary problems through the application of research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.629
GPT teacher head0.703
Teacher spread0.075 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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