Bibliographic record
Abstract
The 1999 signing of the Social Union Framework Agreement, the elimination of government deficits, and an apparent trend to decentralization have increased the focus on Canada's social policy and the manner of its formulation. While disability policy, a key element of social policy that is seldom high on the country's policy agenda, is sharing in the renewed interest, no significant disability policy changes have yet emerged. The Social Union and Disability Policy examines the development of Canadian disability policy and the current political landscape that will influence new policy. It offers an agenda for reform of the disability insurance system and for the provision of supports and services for people with disabilities. The focus is on the impact of governance structures, those now in place and those that might be expected to yield improved policy outcomes while promoting the principles of federalism and democratic oversight. Contributors to the volume are academics Michael Prince (University of Victoria), Roy Hanes (Carleton University) and Allan Moscovitch (Carleton University), NGO representative Michael Bach (Roeher Institute) and social policy analysts Marcia Rioux (York University) and Alan Puttee.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".