Intersectionality Analysis, the Welfare State and Women's Health
Bibliographic record
Abstract
This article applies intersectionality analysis to consider women's health and well-being in Canada's welfare state with attention to those occupying vulnerable social locations. Political and economic structures and processes associated with different forms of the welfare state are responsible for producing these vulnerabilities as they differentially distribute economic and social resources amongst the population. Inequities in these distributions create the social inequalities that act through the social determinants of health to spawn health inequalities. The liberal welfare state -- with its dominant institution being the marketplace -- has higher levels of these inequalities than social democratic and conservative welfare states with rather less public policy effort to reduce them. In addition, the acceptance of neoliberalism as a governing ideology has seen Canadian and other governments further reducing the State role in managing the economy and providing economic and social security to citizens. This has had particular implications for those occupying vulnerable social locations such that the intersectionality concept -- combined with welfare state analysis -- provides a lens which can both explan these social and health inequalities and suggest means to reduce them.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".