Listening for More (Hi)Stories from the Arctic’s Dispersed and Diverse Educational Past
Bibliographic record
Abstract
RésuméAlors que les marques profondes laissées par le système d’écoles résiduelles du Nord canadien refont surface, il est important de poursuivre l’étude des politiques en matière d’éducation en parallèle avec les expériences vécues par les élèves dans des lieux et des contextes d’instruction variés. Dans le cas des Inuits, cette recherche fut incomplète. L’auteure avance qu’il faut approfondir les études sur l’implication du gouvernement fédéral dans les premiers systèmes d’éducation dans les Territoires. Ces travaux devraient prendre en compte les disparités locales et régionales ainsi que les expériences des élèves. En mettant l’accent sur les contradictions et les différents impacts causés par l’éducation dans ces communautés dans le passé, et notamment sur les enseignants sans expérience de la vie nordique, cela permettrait de trouver des manières pour décoloniser l’éducation de nos jours. AbstractAs the widespread and deep impressions left on the Canadian North by the residential school system come to light, it is also important to continue examining educational policies alongside the experiences of students throughout a range of schooling sites and forms. Such research on Inuit schooling has been insufficient. I argue that more detailed educational histories of the federal and early territorial school systems should feature local and regional variability in implementation of policy and in student experience. Illuminating the inconsistent and multifaceted ways education affected communities in the past, particularly for teachers new to the North, serves to illustrate the ways education in the present necessitates decolonizing.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.015 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".