Pigiasilluta oKalagiamik: Culturally Relevant Assessment in Nunatsiavut
Bibliographic record
Abstract
Beginning with a story of travelling between northern communities and the shared experiences of the researchers, the environment, and the animals, this research reports the perspectives of teachers, administrators, and parents on how school-based assessment practices impact Inuit learners in Nunatsiavut, the Labrador Inuit Settlement Area. To adjust to current global social, economic, and environmental challenges (Council of Ministers of Education 2018; OECD 2018; United Nations 2010), mainstream jurisdictions are centering their curricular content and assessment measures on competencies (Alberta 2018; British Columbia 2018; Council of Ministers of Education 2018; OECD 2018; Ontario 2016). Our results show that many of these values are already imbedded in community- and land-based experiences in Nunatsiavut and we argue that the development of assessment practices to capture competencies can help reveal the strengths in culturally relevant curriculum and instruction in Nunatsiavut.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".