Race, Justice, and the Production of Knowledge: A Critical Realist Consideration
Bibliographic record
Abstract
Résumé Les textes à l'étude illustrent des problèmes méthodologiques et pédagogiques généraux considérés par les sciences sociales. En tant qu'exemples illustratifs, chacun de ces textes contribue de manière significative à notre compréhension de la façon dont les sociologues conçoivent et déploient la «race» comme catégorie analytique et comment cela influe sur la production des connaissances au sujet du contrôle de la criminalité et de la justice sociale. Ainsi, les textes montrent, en général, comment des catégories analytiques sont traités dans l'enseignement et la recherche. Adoptant une approche comparative à partir de trois textes récents, cet essai pose qu'on ne peut éviter de considérer les enjeux épistémologiques provenant de l'emploi de catégories analytiques centrales et que les tentatives de le faire mènent à un engagement passif plutôt qu'actif avec l'objet de l'analyse. Au surplus, des approches passives ne servent guère une enquête critique en sciences sociales.
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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.010 | 0.078 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".