Inuit Voices on Quality Education in Nunavut: Policy Implications
Bibliographic record
Abstract
This paper is based on a research that explored how Inuit community members in Nunavut Territory, Canada, conceptualized quality education in the socio-cultural context of the territory. Data were collected through telephone interviews of 13 Inuit community members in Nunavut and document reviews both of which were conducted in 2010. The data analysis showed that Inuit community members are r gravely concerned with:(1) the low grade twelve graduation rates and high dropout rates in the territory schools;(2) School improvement planning that engages Inuit communities; (3) Integration of school with the larger community; (4) Communicative engagement with parents and other community stakeholders; (5) Culturally relevant school programming and pedagogy; and (6) Culturally appropriate disciplinary methods. In the conclusion, the paper spells out the policy implications of the findings.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.012 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".