Bibliographic record
Abstract
Introduction Canadians developed their version of the welfare state in the context of a vibrant federal state, with strong governments at both the federal and provincial level. Their experience highlights in fascinating ways the reciprocal interplay between federalism and social policy. In comparative context, the Canadian case underscores the need for more nuanced analysis than is found in much of the comparative literature of the welfare state, which is summarized in the introduction to this book. Attention normally focusses on simple dichotomies: federal versus non-federal, centralized versus decentralized, concentrated power versus multiple veto points. It is widely argued that federal, decentralized and/or fragmented decision-making inhibited the expansion of the welfare state in the twentieth century, but has slowed the processes of restructuring in the contemporary period. Such propositions do find echoes in Canada. For example, decentralization helped to slow the pace of development in the first half of the twentieth century. The primary lessons to be drawn from the Canadian experience, however, emerge from the modern social programmes put in place in the second half of the twentieth century. Canada did not develop a single, integrated public philosophy of federalism in this period, and federal–provincial relations in social policy incorporated three distinct models, each with its own decision rules. At any point in time, governments were shaping or reshaping different programmes according to different rules and processes. Canada therefore constitutes a natural laboratory in which to analyze the implications of different models of federalism.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".