Canadian Non-Energy Exports: Past Performance and Future Prospects
Bibliographic record
Abstract
Canada has continued to lose market share in the United States since the Great Recession, beyond what our bilateral competitiveness measures (relative unit labour costs) would suggest. In this context, we have studied 31 non-energy export categories to assess their individual performance against a category-specific foreign activity measure or benchmark, and to identify which export subaggregates will likely be supported by the recent depreciation of the Canadian dollar. Our main findings are: (i) among the 31 subsectors of non-energy exports, about half (in value terms) have either been performing as expected or outperforming their benchmarks; (ii) the remaining subsectors have lagged their benchmarks, mainly owing to longer-term structural declines; (iii) around half of the subsectors appear to be quite sensitive to persistent movements in the exchange rate; and (iv) about half of the non-energy export subaggregates are anticipated to lead the recovery, including those likely to benefit from robust growth in U.S. construction, U.S. investment in machinery and equipment, and/or the recent depreciation of the Canadian dollar.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".