Bibliographic record
Abstract
En nous appuyant sur une revue de la littérature criminologique essentiellement américaine à propos des gangs de rue, nous interrogerons la construction ethnicisante, voire racialiste des conduites délinquantes collectives des jeunes issus des minorités, en prenant l’exemple des gangs afro-américains. Ceci en ramenant cette construction à deux lignes d’analyse dont la première est celle du contexte historico-national de production de l’objet « gangs de rue » et de l’ethnicité qui y est associée, avec les notions de « relations raciales » et d’« interethnicité ». La seconde est celle de l’agir ethnique, s’observant sur les deux faces interne et externe de la communalisation. C’est la construction ethnique de l’individu dans le rapport qu’il entretient avec sa communauté idéelle d’appartenance, sa culture et son histoire, et simultanément, le rapport qu’il entretient avec les autres, dans un double mouvement de désignation et d’autodésignation, traçant une frontière labile, parfois statique, entre les « eux » et les « nous ».
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".