Bibliographic record
Abstract
It is widely recognized that productivity growth is the key driver of long-run increases in living standards. Therefore, a slowdown in productivity growth is a major cause for concern. This has in fact been the situation in Ontario since 2000. After advancing at a 1.9 per cent average annual rate between 1987 and 2000, business sector productivity growth has fallen to 0.5 per cent per year between 2000 and 2012, the second lowest growth rate among the provinces. Indeed, given the relative size of Ontario’s economy, the province’s weak productivity growth has largely been responsible for Canada’s overall poor productivity performance. The objective of this report is to explain the slowdown in productivity growth in Ontario since 2000. The report provides an overview of the productivity performance of the Ontario economy, with a focus on the 2000-2012 period. The report also examines both the supply-side and demand-side factors that influenced Ontario’s productivity performance. The main cause of Ontario’s lackluster productivity growth is found to be the deterioration of external demand conditions. The drop in international exports, due to weak demand growth in the United States, loss of cost competitiveness linked to the appreciation of Canadian dollar and increasing international competition, played a direct role in the slowdown in Ontario’s productivity growth.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".