Bibliographic record
Abstract
In Money in Their Own Name, Wendy McKeen examines the relationship between gender and social policy in Canada from the 1970s to the 1990s.Providing a detailed historical account of the shaping of feminist politics within the field of federal child benefits programs in Canada, she explores the critical issue of why the feminist vision of the 'social individual' failed to flourish.Canadian social policy has established women's access to social benefits on the basis of their status as wives or mothers, not as individuals in their own right.In her analysis, McKeen discusses this persistent familialism that has been written and rewritten into Canadian social policy, and shows how this approach reinforces women's dependency.She further demonstrates the lack of contest by the women's movement toward this dependent status, and the consequent erasure of women from social policy.McKeen effectively weaves together sociological theory with concrete examples of political struggle.She uncovers overlooked aspects of Canadian social policy politics and subsequently extends our understanding of the political process.At the same time, by synthesizing the concepts of discourse, agency, and policy community, she offers a new analytical tool for understanding how the political interests of actors are shaped.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.691 | 0.405 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".