Small Schools in a Big World: Thinking About a Wicked Problem
Bibliographic record
Abstract
The position of small rural schools is precarious in much of rural Canada today. What is to be done about small schools in rural communities which are often experiencing population decline and aging, economic restructuring, and the loss of employment and services? We argue this issue is a classic "wicked" policy problem. Small schools activists have a worldview that is focused on maintaining infrastructure and even community survival, while school boards are mandated to focus on the efficient provision of educational services across wider geographies. Is it even possible to mitigate the predictable conflict and zero-sum games that arise with the decision to close small schools? That is the subject of this paper, which draws on poststructural and actor network theory. We suggest that wicked problems cannot be addressed satisfactorily through formulas and data-driven technical-rational processes. They can only be addressed through flexible, dialogical policy spaces that allow people who have radically different worldviews to create dynamic, bridging conversations. Fundamentally, we argue that what is required are new spaces and modes of governance that are sufficiently networked, open, and flexible to manage the complexity and the mutability of genuinely participatory democracy.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.069 |
| Scholarly communication | 0.016 | 0.035 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.008 |
| 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".