Incorporation of Inuit Qaujimanituqangit, or Inuit Traditional Knowledge, into the Government of Nunavut
Bibliographic record
Abstract
Defining the term “indigenous knowledge” is a difficult process as it encompasses different things to different people. Variations on the term are about as many as there are interpretations of the concept. Inuit Qaujimanituqangit, or “Inuit traditional knowledge,” is a topic of much interest for the Government of Nunavut, which has publicly stated that it will use Inuit Qaujimanituqangit (IQ) as its foundation. IQ, in this context, becomes more than a purely intellectual exercise: from legislation and policy development, to program design and delivery, to needs assessment, statistical analysis, etc. IQ has huge practical ramifications on public administration in Nunavut. The anthropological element of IQ subsides somewhat, and contemporary political and social development issues come to the fore. IQ, then, becomes a question and means of actualizing social and political aspirations of a people. In this paper, I will talk a bit about the IQ work in the Department of Sustainable Development, the policy and program development framework that we developed for the Department, and about the model and set of guiding principles upon which we base our work.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".