Bibliographic record
Abstract
This paper investigates the conditional convergence of both human capital indicators and nominal per capita income across Canadian provinces in a panel-data empirical framework. Long-run relative provincial steady states are determined by relative rates of urbanization, one-time shocks to Quebec’s and Alberta’s relative steady states, and a Nova Scotia fixed effect. Indicators of relative human capital ratios appear to have converged following a pattern that is common and similar to per capita income but with two notable exceptions. First, in Alberta, the 1973 oil shock contributed to the rise in per capita income but its effect on human capital is significant only for females. Second, human capital appears to remain concentrated in the relatively poor province of Nova Scotia. Two notable findings come out of the analysis. First, nominal income disparities at the provincial level appear to be real, not just nominal. Second, the analysis suggests that at the regional level, human capital is a necessary but not sufficient condition for being wealthier in the long run.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".