Global Competitiveness and Canadian Sectoral/Regional Labour Productivity Differences
Bibliographic record
Abstract
This paper evaluates the extent to which the decrease in total factor productivity growth that is alleged to have occurred in the last few years is also reflected in corresponding decreases in labour productivity growth, among key provinces and sectors of the Canadian economy. The analysis is based upon non-parametric productivity comparisons, for the 1984-1998 period. Data envelopment analysis is the methodological tool selected for the measurement of total factor productivity and hence of operational effectiveness to assess the extent to which sectoral productivity differences across Canadian regions represents a barometer of global competitiveness. The evidence indicates that labour productivity is growing. Factors associated with economies of scale appear to be the main source of inefficiency, as expected in a spatial setting. These inefficiencies are reflected mostly in increasing returns to scale, which enhances the competitiveness potential of the regions' economic base and of the industries in their midst.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".