Canadian Labour Market Dispersion: Mind the (Shrinking) Gap
Bibliographic record
Abstract
Shocks to a currency area can and often do have asymmetric impacts on its regions that, in the absence of perfect labour mobility, lead to gaps in relative labour market performance. Witness, for example, the effects of the 2008/09 recession and subsequent financial crisis in Europe on the dispersion of employment rates across the euro area – and to a lesser extent the United States. These interregional labour market gaps can persist, as has traditionally been the case for Canadian provinces. From 1976 to 1997, the mean absolute dispersion between any one province and the national employment rate was 5.5 percentage points – significantly higher than the corresponding measure in the United States. Since then, however, the Canadian metric has fallen consistently and in 2015 was not that different than its U.S. equivalent. Despite the impacts of commodity price booms from 2003 to 2008 and 2010 to 2014, the 2008 Great Recession, and the recent sharp decline in commodity prices on the Canadian economy, Canada’s provincial labour markets are less dissimilar today than at any point in at least the past 35 years. We find that reductions in the dispersion of provincial employment rates in the mid-1990s and 2000s are mostly concentrated among women and those in the 25 to 44 age group. Furthermore, evidence suggests that the tighter dispersion of employment rates has not been driven by stronger employment growth in previously weak regions of the country. Rather, it has mostly occurred as regional population growth has increasingly responded to labour market conditions. In other words, labour is being more efficiently reallocated to the regions of the country that have the tightest labour markets and away from those with excess labour supply. The dispersion of both unemployment and participation rates has fallen, contributing to this trend.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".