Immigration, Attraction or Local Production? Some Determinants of Local Human Capital Change in Canada
Bibliographic record
Abstract
It has become almost a truism to claim that local development is strongly dependent on a region’s endowment in human capital (HC). Endogenous growth \ntheory, elaborated principally at the national scale, has provided the theoretical \nframework for this idea, and recent work by Richard Florida has popularised \nthe notion, in particular the idea that regions should attempt to attract mobile talent. In this paper we explore certain regional determinants of local HC \ngrowth (as measured by the number of degree holders), distinguishing between \ninternational immigration, internal migration and endogenous increases. We \nshow that each type of HC growth responds to di" erent geographic and local \ndeterminants and that there exist some basic geo-structural determinants of \nHC # ows that are not related to a locality’s particular amenities. Finally, a reverse analysis of amenity variables as basic determinants of internal migration \nshows a possible shi$ in attractiveness from mostly regional factors (certain \nparts of Canada are more attractive than others) to structural ones of size and \ncentrality
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".