HOW IMPORTANT IS A SCHOOL? EXAMINING THE IMPACT OF REMOTENESS FROM A SCHOOL ON CANADIAN COMMUNITIES’ ATTRACTION AND RETENTION OF SCHOOL-AGE CHILDREN
Bibliographic record
Abstract
Many Canadian communities, especially rural communities, are concerned about youth outmigration as a cause of population decline, which is associated with fewer services and amenities. Proponents of keeping underattended schools open argue that removing a school from the community means that fewer families will want to live there, and that more families will consider leaving. Others view school closures as a rational response to population decline. Still other perspectives complicate the correlation between schools and population, noting phenomena such as children “learning to leave” and “place attachment” that modulate the temptation to move away. This paper offers an empirical test of discursive connections between school closures and mobilities by studying the population change of school-age children in Canadian census subdivisions indexed by distance to the nearest school. Based on this method, we conclude that there is a positive correlation between the school-age population in a community and proximity to a school in that community. Although our data do not answer the question of whether school closures cause population decline, or such a decline causes school closures, or both, we provide a quantitative foundation on which to ask it.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".