A Perspective on Future Productivity Growth in Canada
Why this work is in the frame
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Bibliographic record
Abstract
In the first contribution to the Symposium included in this volume on Future Productivity Growth in Canada, Thomas Wilson of the University of Toronto presents forecasts based on the FOCUS macroeconometric model of the Canadian economy. This model projects labour productivity growth to grow at an average annual rate of 1.7 per cent over the 2002-2025 period. Wilson is somewhat more optimistic, seeing labour productivity growth of around 2 per cent per year. Reasons behind his more rosy scenario include a greater pace of capital deepening due to much slower labour force growth, the realization of productivity gains from past investments in information and communications technologies, a mitigation of future business cycles due to greater use of automatic stabilizers, and continued benefits from trade liberalization.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it