COMBINING THE VIEWS OF “BOTH WORLDS”: SCIENCE EDUCATION IN NUNAVUT PIQUSIIT TAMAINIK KATISUGIT
Bibliographic record
Abstract
This paper reports on several phases of a five-year science education development project in Nunavut, Canada. The project, in its entirety, was established as a Pilot Program for Nunavut schools in effort to understand school community aspirations for science education and potential contributors and impediments to fostering the realization of identified goals. This paper focuses on the cases of three Inuit school communities in identifying and achieving their aspirations for science education. This paper describes the goals collaboratively identified and the processes utilized to work towards the realizations of such goals. Of importance is the identification by the school communities to offer an educational experience that combines the knowledge, processes and values of "both worlds" (western science and Inuit Qaujimajatuqangit) and to employ both traditional and contemporary methods for implementing and evaluating the success of the project. Finally, based upon the outcomes of this project, suggestions are provided for supporting developments in other jurisdictions aspiring to see the realization of local and Indigenous aspirations for science education. Of critical importance to seeing such efforts realized are the policy and leadership conditions manifest at the school-community, divisional and territorial level for fostering culture-based education programs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".