Schools that Don’t Close: Possible Places and Spaces for Progressive Teaching, Learning, and Research
Bibliographic record
Abstract
Small schools and their communities contribute to an important, though threatened, knowledge base. The threat adheres in underlying technologies (conceptual and material) that propel the capitalistic world towards the rationalization of all aspects of human activity. In education, this appears in the consolidation of small schools and ever larger units of organization. From three studies of Newfoundland coastal communities, I describe schools that were deemed to be “necessarily existing.” Because of their isolated location, students from the schools could not be transported to larger centres. While reporting both positive and negative features of actual small, rural schools, I argue against hasty school closures and point, instead, to rural school and community opportunities for “place, voice, and space-based” teaching, learning, and research. Small, rural schools can be pivotal in leading Canadian education from its deeply rooted, market-based ideology to progressive and socially relevant practices that embrace lifelong learning, community involvement, and ecological awareness and action.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.042 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| 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".