Au-delà des déterminismes biologique et classiste dans l’explication des inégalités scolaires
Bibliographic record
Abstract
Cette critique appartient à une série de trois articles de la section Forum sur le livre de Barnes (2016), Are They Rich Because They’re Smart? Elle analyse les arguments dont Barnes se sert pour déconstruire le point de vue défendu par Herrstein et Murray (1994) dans The Bell Curve . Pour Barnes, le discours de Herrstein et Murray remplit une fonction politique, et non scientifique : il sert à justifier, avec des arguments biologiques faux, les inégalités économiques dont la soi-disant méritocratie profite, alors que l’explication des inégalités socioéconomiques et culturelles est sociopolitique. La réponse de Barnes, centrée sur la lutte des classes sociales, minimise toutefois le rôle des pratiques et des interactions des agents dans l’analyse des rapports sociaux inégalitaires.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".