Bibliographic record
Abstract
Andrea Ritchie est une immigrante noire et lesbienne dont l’engagement, la recherche et les écrits portent sur le contrôle policier des femmes et des personnes LGBT noires et de couleur depuis deux décennies. Elle est présentement chercheuse en résidence au Barnard Center for Research on Women , travaillant sur l’axe Criminalisation, race, genre et sexualité, et elle a été boursière senior en 2014 du fonds Soros Justice . Elle a récemment publié le livre Invisible No More : Police Violence Against Black Women and Women of Color (Beacon Press, 2017). Elle est la co-auteure de deux autres livres, Say Her Name : Resisting Police Brutality Against Black Women (2016) et Queer (In)Justice : The Criminalization of LGBT People in the United States (2011). Née à Montréal, elle a vécu et milité à Toronto pendant huit ans dans les années 1990. Elle réside aujourd’hui entre Chicago, Brooklyn et New York.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".