Disarmed and Disadvantaged: Canada's Workers Need More Physical Capital to Confront the Productivity Challenge." C.D. Howe Institute e-brief
Bibliographic record
Abstract
Canadian workers have enjoyed less robust investment in plant and equipment than their counterparts in the United States and other major developed countries over the past 15 years. And notwithstanding Canada’s relative economic resilience through the recent slump, the per-worker investment gap vis-à-vis other countries appears to have widened. Policy measures to foster more investment in physical capital would give Canadian workers the tools to match foreign rivals and achieve high and growing incomes in the years ahead. Policymakers should increase domestic exposure to global competition and improve international tax provisions to attract inbound foreign investment and encourage repatriation of earnings by Canadian companies abroad. A key lesson from Canada’s own experience and from economic development around the world is that business investment in plant and equipment is critical to raising output and living standards. Increased work effort contributes negligibly to rising incomes over time: what matters much more are new machinery, equipment and buildings, and the technological innovations and organizational improvements they entail. 1
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.004 |
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".