Bibliographic record
Abstract
Abstract.This article demonstrates that though the political nature of race is evident and constitutes an important area of research, there is a dearth of literature on race in English Canadian political science particularly as compared to other social sciences. The article provides explanations for this disciplinary silence, including methodological fuzziness, dominant elite-focused and colour-blind approaches to the study of politics, and the prevalence of ideas and foci about the nature of Canadian politics. In order to avoid the danger of disciplinary lag, it concludes with several ways of addressing this disparity between the political science and the society it purports to analyze. Résumé.Malgré l'essence politique évidente du concept de «race» et son importance indéniable comme sujet de recherche, la littérature de science politique canadienne-anglaise s'y attarde très peu, surtout en comparaison des autres sciences sociales. L'article explique les causes de ce silence disciplinaire. Celles-ci incluent un flou méthodologique, une approche surtout centrée sur l'élite, une perspective «daltonienne» concernant l'étude de la politique, ainsi que la prédominance de certaines idées quant à la nature de la politique canadienne. Afin d'éviter un danger de lacune disciplinaire, l'article propose des solutions permettant de réduire l'écart entre la science politique et son objet d'étude, soit la société réelle.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.027 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".