Bibliographic record
Abstract
Cet article analyse les différentes barrières que rencontrent les coiffeurs descendants d’immigrés, originaires du Maghreb et de l’Afrique subsaharienne, au cours de leur carrière pour se faire une place dans le métier et les tentatives qu’ils mettent en place pour infléchir cette situation. Il restitue notamment les différentes injonctions corporelles ou langagières exigées par la profession. Pour se rapprocher d’un « idéal caucasien » recherché par les collègues de travail et les employeurs, les coiffeurs sont par exemple sommés de se lisser les cheveux ou de changer de prénom. La figure de la clientèle vient justifier ces exigences de la part des employeurs. Cet article montre également comment, dans une profession constituée majoritairement de femmes, être un homme tend à atténuer cette identité raciale qu’on leur appose. Mais ces tentatives de mise en conformité à cet idéal professionnel ne signifient pas acceptation du racisme. Des formes de résistance à cette traduction du social apparaissent et leur permettent de retrouver une certaine estime de soi.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
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".