Bibliographic record
Abstract
Established in 1940 in response to the Great Depression, the original goal of Canada’s system of unemployment insurance was to ensure the protection of income to the unemployed. Joblessness was viewed as a social problem and the jobless as its unfortunate victims. If governments could not create the right conditions for full employment, they were obligated to compensate people who could not find work. While unemployment insurance expanded over several decades to the benefit of the rights of the unemployed, the mid-1970s saw the first stirrings of a counterattack as the federal government’s Keynesian strategy came under siege. Neo-liberalists denounced unemployment insurance and other aspects of the welfare state as inflationary and unproductive. Employment was increasingly thought to be a personal responsibility and the handling of the unemployed was to reflect a free-market approach. This regressive movement culminated in the 1990s counter-reforms, heralding a major policy shift. The number of unemployed with access to benefits was halved during that time. From UI to EI examines the history of Canada’s unemployment insurance system and the rights it grants to the unemployed. The development of the system, its legislation, and related jurisprudence are viewed through a historical perspective that accounts for the social, political, and economic context. Campeau critically examines the system with emphasis upon its more recent transformations. This book will interest professors and students of law, political science, and social work, and anyone concerned about the right of the unemployed to adequate protection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.015 |
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".