Bibliographic record
Abstract
The danger in politicians promoting the idea that “Dutch Disease” is responsible for the decline of the Ontario manufacturing sector is that the suggestion implies that Canada’s manufacturing sector will bounce back if only we could slow down oil sands development, or if the Canadian dollar were to devalue. In reality, evidence suggests that the decline in Ontario manufacturing is the result of long-term structural changes in the economy, independent of the rise of the country’s natural-resource sector and the rising dollar. And the sooner policymakers realize that, and stop blaming the decline in manufacturing on Dutch Disease (which holds that a booming natural-resource sector that drives up our dollar makes our manufacturing exports less competitive) the sooner they can get to work on helping manufacturing-dependent regions transition to the evolving economy. A closer analysis of Canada’s manufacturing sector shows that jobs in that sector have been disappearing across the country since the end of the Second World War, with the sector’s share of employment falling dramatically well before rapid development began to take hold in the oil sands, and back when Canada’s dollar was still worth far less than the American dollar. It is a trend that has been occurring among most of our OECD peers, including the United States, which may be due to the widespread reallocation of production to lower cost countries. But it is also true that Canada’s manufacturing productivity performance in particular has been declining for a generation, with especially poor performance in the last decade, when labour productivity in Canada grew at just a quarter of the U.S. rate. Meanwhile, capital investment that may have improved the competitiveness of Canadian manufacturing has been anemic. Yet there is no particular reason to lament the scaling-down of manufacturing jobs in Ontario. The province remains just as economically important, as a share of national GDP, as it was 30 years ago, and its unemployment rate has remained roughly in line with the Canadian average. Often the manufacturing jobs that disappear soonest are low-skill, low-paying jobs. Indeed, those workers that have remained in the sector have done very well, with the growth in weekly earnings in the Ontario manufacturing sector outpacing the national average. It would be a grave mistake for Ontario’s policy-makers to argue in favour of hampering Canada’s oil sands development in hopes that it might devalue the dollar and revive their province’s shrinking manufacturing base. It would harm the national economy and yet, judging by the evidence, may do nothing to add jobs at Ontario’s factories. Instead, Ontario’s policymakers should accept that those jobs might never return, and instead, focus their energies on finding ways to encourage growth in high-skill, high-paying jobs in other sectors that offer more promise.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.002 |
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".