Bibliographic record
Abstract
There is a growing recognition that existing theories on, and approaches to, health inequities are limited in their ability to capture how these inequities are produced through changing, co-constituted, and intersecting effects of multiple forms of oppression. Intersectionality responds to this problem by considering the interactions and combined impacts of social locations and structural processes on the creation and perpetuation of inequities. It offers unique insights into, and possible solutions to, some of Canada’s most pressing health disparities. This volume brings together Canadian activists, community-based researchers, and scholars from a range of disciplines to apply interpretations of intersectionality to health and organizational governance cases. By addressing specific health issues, this book advances methodological applications of intersectionality in health research, policy, and practice. Most importantly, it demonstrates that health inequities cannot be understood or addressed without the interrogation of power and diverse social locations and structures that shape lives and experiences of health.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.022 | 0.004 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".