EDUCATIONAL PRIOROTIES AND CAPACITY: A RURAL PERSPECTIVE
Bibliographic record
Abstract
This study examined the congruence between the priorities of the Manitoba govern‐ ment’s Kindergarten to Senior 4 (K‐S4) Education Agenda for Student Success and prior‐ ities of stakeholders in a rural Manitoba school division, and the division’s capacity to achieve them. Capacity included three components for success: Legitimization of Al‐ ternatives, Diverse Networks, and Resource Mobilization. The findings suggest that the theoretical conceptualizations of how rural areas develop and/or thrive have yet to be refined. Many of the findings coincide with Howley’s (1997) ideas that school reform efforts tend to essentialize schooling across contexts, for reasons that do not always reflect local purposes, interests, and/or capacities. Key words: rural education, school policy, school improvement Cette étude porte sur la congruence entre les priorités du Programme d’action en éducation favorisant la réussite chez les élèves de la maternelle au secondaire 4 (M‐S4) du gouvernement du Manitoba et les priorités identifiées par des groupes d’intéressés au sein d’une division scolaire rurale de la province et la capacité de cette division de les réaliser. Cette capacité comprenait trois volets : la légitimation des autres options possibles, les réseaux diversifiés et la mobilisation des ressources. Les résultats semblent indiquer que les conceptualisations théoriques du mode de déve‐ loppement des régions rurales ont besoin d’être raffinées. Bon nombre des conclu‐ sions coïncident avec les idées de Howley (1997) selon lesquelles les efforts de réforme scolaire ont tendance à essentialiser l’éducation pour des raisons qui ne reflètent pas toujours les objectifs, les capacités et/ou les intérêts locaux. Mots clés : éducation en milieu rural, politiques scolaires, amélioration de l’école
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".