Diversity and employment growth in Canada, 1971– 2001: can diversification policies succeed?
Bibliographic record
Abstract
In this paper, we explore the link between diversity in the local economy, the process of diversification and employment growth. To do so, we first examine diversification trends between 1971 and 2001 across 382 Canadian areas (urban and rural). We then examine whether or not the more diversified areas display faster employment growth. Over some periods and for some types of area they do, but over other periods they do not. Furthermore, there is no clear link between the process of diversification and growth. Also, proximity to a large diversified economic unit (metropolitan areas) tends to be associated with growth; thus, it is not only the local characteristics of regions that determine their growth levels. Our evidence suggests that economies associated with diversity can occur concurrently with economies associated with specialisation. In the light of these complex relationships, we conclude that diversification policies are difficult to justify on the grounds of employment growth and would in any case be difficult to implement successfully due to the overall inertia observed in diversity levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".