The Potential Contribution of Aboriginal Canadians to Labour Force
Bibliographic record
Abstract
Investing in disadvantaged young people is one of the rare public policies with no equity-efficiency tradeoff. The objective of the paper is to estimate the potential contribution of Aboriginal Canadians to labour force, employment, output, and productivity growth in Canada over the 2006-2026 period. We first examine the developments in educational attainment, labour force participation and income of aboriginal and non-aboriginal Canadians between 2001 and 2006 using the recently released 2006 census data. Then, using the methodology developed in Sharpe, Arsenault and Lapointe (2007), we estimate the potential benefit for the Canadian economy of increasing the educational attainment level of Aboriginal Canadians. We extend the original analysis five years to cover the 2006-2026 period. We find that increasing the number of Aboriginals who complete high school continues to be a low-hanging fruit and that significant and far-reaching economic and social benefits can still be realized. We present estimates of the extent to which increased Aboriginal education could contribute to alleviating two of the most pressing challenges facing the future of the Canadian economy: slower labour force growth and lackluster labour productivity growth. We find that under certain scenarios, a rapid convergence
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".