Bibliographic record
Abstract
Cette recherche examine les interactions entre logiques communautaires, économiques et normatives au sein de petites et moyennes entreprises implantées dans des quartiers prioritaires en France. À partir de deux études de cas menées dans les secteurs du transport et de la sécurité privée, elle mobilise une méthodologie qualitative fondée sur dix-neuf entretiens (non directifs et semi-directifs), une observation non participante et l’analyse de documents internes. L’analyse thématique, conduite selon le cadre d’analyse de Gioia et appuyée sur une triangulation méthodologique, permet de comparer les deux contextes à travers des thématiques communes liées à la diversité, aux pratiques managériales et au sentiment d’appartenance. Les résultats montrent que les dirigeants articulent proximité sociale, performance économique et conformité institutionnelle pour construire leur modèle managérial. Les appartenances ethniques et religieuses, initialement sources de cohésion, se transforment sous l’effet de la formalisation et de la professionnalisation. La réglementation devient alors un levier d’inclusion encadrée, marquant la transition d’un management communautaire fondé sur la solidarité vers un management inclusif centré sur la norme, la compétence et la reconnaissance professionnelle.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.027 | 0.039 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.607 | 0.338 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".