What we know and don't know about small schools: A view from Atlantic Canada
Bibliographic record
Abstract
In the 1913-1914 school year, the number of one-room schools in the United States swelled to an estimated 212,000. Yet, at the same time, educational reformers were leading a much publicized campaign to abandon these small schools. Among the weaknesses cited were the inadequate recruitment and supervision of teachers, out-of-date curricula, haphazard school attendance, limited course offerings, poor academic performance, and unsanitary practices. What children needed in the new industrial age, the reformers argued, were larger schools with age-graded classrooms, workshops, gymnasiums, cafeterias, diversified course offerings, and much more. Eventually the reformers prevailed. Most U.S. one-room rural schools were consolidated and the buildings sold, used for other purposes, or abandoned. Yet small schools have not entirely disappeared from the educational landscape. In the following article, Michael Corbett, a professor of education in Nova Scotia, explores current international research on the effectiveness of small and large schools, the hotly contested trend to close small Atlantic Canadian schools, and efforts to preserve these schools as essential to the well-being of rural communities.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.055 | 0.027 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".