Panel discussion Recent Developments in the Canada-U.S. Unemployment Rate Gap: Changing Patterns in Unemployment Incidence and Duration Presented at the CEA Meetings
Bibliographic record
Abstract
Since the mid-1990s, the performance of the labour market in Canada has improved both in absolute terms and relative to the United States. In 1995 the unemployment rate in Canada averaged 9.6 per cent, a full 4.2 percentage points above the U.S. rate. Seven years later in 2002, the unemployment rate in Canada was 7.6 per cent, compared to 5.8 per cent in the United States – a gap of only 1.8 percentage points.2 Other labour market indicators also reflect this relative improvement. The employment-to-population ratio, for example, rose in Canada from 58.8 per cent in 1995 to 61.5 per cent in 2002, while in the United States this ratio fell marginally over the same period from 62.9 per cent to 62.7. The relative improvement in Canada’s labour market in recent years contrasts with the relative underperformance over the previous 15 years. After tracking the U.S. unemployment rate quite closely through the 1950s, 1960s and 1970s, the unemployment rate in Canada averaged about 2 per centage points above the U.S. rate in the 1980s, and this gap widened to about 4 percentage points by the mid-1990s. 1 We are grateful for helpful comments and suggestions from Bob Fay, John Helliwell and participants at the June 2003 CEA Meetings in Ottawa. The views expressed in this comentary are our own and no responsibility for them should be attributed to the Bank of Canada. 2 There are a number of measurement issues when comparing the Canada and U.S. unemployment rates. Statistics Canada suggests that differences in methodology account for about 0.6 percentage points of the current unemployment gap, which would put the average gap measured on a comparable basis at 1.2 per cent in 2002.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.003 |
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".