Bibliographic record
Abstract
Ontario's private sector has had zero productivity growth in the latest six year period. Ontario performed much worse than the rest of Canada or the United States. This is obviously a cause for concern. Productivity is an important measure of progress in the economy, as it is associated with rising standards of living in the long run.\n\nThe question is whether this observation about productivity is significant in its own right, or if it is more a symptom of the overall state of the economy. The Ontario economy has been hit by major external shocks, resulting in plunging exports and a declining private sector employment rate. Is productivity an independent causal factor, or merely the residual outcome of weak demand?\n\nThis paper examines the issue through detailed sectoral data. It examines the diversity of productivity performance in about 50 industrial sectors. The picture that emerges is that the overall productivity growth rate is not really representative. It is the random outcome of a wide range of underlying variation. There are some important sectors (e.g., retail trade and finance) that have maintained decent productivity growth. There are some sectors, especially in manufacturing, where the level of productivity is currently far below its previous level. This is not merely weak growth, but decline. In some industries (e.g., steel), some of the largest players have shut down, essentially changing the character of that sector even though the name remains the same.\n\nOverall, the implication is that the weakness of productivity is caused by weak aggregate demand. Historically, productivity growth has been pro-cyclical, being positively correlated with demand growth. Strong demand creates economies of scale and distributes overhead costs over a larger base. The weakness of demand in recent years has also been associated with compositional shifts in the economy. Employment and output have plunged in manufacturing (whose level of productivity is above the economy-wide average), while it has grown in some service sectors with below average productivity. Such compositional shifts would reduce the average productivity of the economy even if there was no change in the productivity of any individual sectors.\n\nOntario had positive productivity growth in the service sector, but underperformed the strong growth found in the rest of Canada. Here, too, the explanation is likely found in diseconomies of scale due to weaker demand. For example, the higher productivity growth in retail and wholesale trade in the rest of Canada was associated with growth in sales that was two-thirds higher than in Ontario over the past six years.\n\nThe weakness of demand in Ontario is largely due to falling exports, caused by the high Canadian dollar and the weak US economy. This can be considered in a positive light. While a strong rebound in exports does not appear to be around the corner, the worst is probably behind us. There should be a continuing gradual improvement in exports in the coming years, leading to some increase in productivity growth. The Ontario government should focus its policy levers, which are admittedly constrained, on helping to further the upward trend in exports.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".