Recent Productivity Developments in Canada and the United States: Productivity Growth Deceleration versus Acceleration
Bibliographic record
Abstract
Since 2000, productivity growth in Canada and the United States have followed markedly different paths. In the second article, Andrew Sharpe of the Centre for the Study of Living Standards finds that the remarkable productivity growth experienced in the United States in the past two years is most likely evidence of a post- 2000 productivity growth acceleration, similar to the post-1995 acceleration. The source of this second acceleration appears to be the rapid pace of technological change, fostered by pressures on firms to cut costs, organizational changes that allow the productivity-enhancing potential of ICTs to be realized, and the cheapening of the price of capital goods relative to labour. In contrast, productivity growth in Canada decelerated after 2000. The source of the difference with the U.S. performance has been the labour market, with employment declining in the United States but showing strong increases in Canada. Sharpe states that Canada’s poor productivity growth since 2000 has largely been a cyclical phenomenon, and that Canadian productivity growth should rebound as the economy recovers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".