Faut-il travailler son corps pour réussir un entretien d’embauche ? La place de l’apparence physique dans les manuels d’Aide à la recherche d’emploi
Bibliographic record
Abstract
La relation entre corps et emploi constitue un enjeu explicite pour les politiques publiques, notamment à travers la législation en matière de discrimination. Ainsi, depuis le 16 novembre 2001, « aucune personne ne peut être écartée d’une procédure de recrutement […] en raison […] de son apparence physique ». Cet article s’intéresse aux ouvrages de préconisation à l’usage des chercheurs d’emploi, censés faciliter leurs accès ou leur retour au marché du travail. Comment parviennent-ils à assurer leur activité de conseils au regard du cadre législatif antidiscriminatoire français ? Comment traitent-ils du corps des candidats sans nuire à la crédibilité du processus de recrutement ? Quelles normes corporelles véhiculent-ils ? Cet article répond à ces questions en s’appuyant sur l’analyse de contenu de 31 manuels.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".