Bibliographic record
Abstract
This report examines the impact on Employment Insurance (EI) eligibility of the increase in the entrance requirement for new entrants and re-entrants, under Bill C-12, from 20 to 26 weeks (or equivalent 910 hours). The results of the analysis suggest that:\n\na) On average, about 36,500 new entrants/re-entrants were affected negatively each month in 1997 — i.e. did not qualify for EI, but would have qualified under the old rules.\n\nb) An additional 9,100 new entrants/re-entrants could have also been affected negatively each month, but were able to work additional hours to meet the higher entrance requirement.\n\nc) As a result, the average monthly number of regular beneficiaries in 1997 was reduced by about 5.8 percent (from a potential 633,200 to 596,700); correspondingly, total regular benefit payments in the entire 1997 were lower by about $520 million.\n\nd) The new rules for new entrants/re-entrants had a greater negative effect on claimants with monthly family incomes under $2,000, and those who received social assistance since\nthe loss of their job.\n\nThe above results are based on an ex ante analysis of the Canadian Out of Employment Panel (COEP) survey. The cohort analyzed consists of those individuals who terminated a\njob in the last quarter of 1995. To reconstruct work and claim histories, the COEP data were supplemented by the respondents’ Records of Employment and EI Status Vectors.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".