Bibliographic record
Abstract
The Métis are a post-contact Indigenous People whose origins lie in the buffalo hunting economy of the late 18th-/early 19th-century northern plains, where their mobile society flourished, in relations with their First Nations relatives, by the mid-19th century. Their culture evolved through a distinctive combination of identity, language, land tenure, economic niche and family kinscapes. Much of the literature pertaining to Métis populations has taken for granted the self-identification by respondents of large-scale surveys and the census as a basis for estimating socio-demographic and epidemiological characteristics. This is deeply problematic to the extent that it diminishes the power of Métis governments (provincially) to provide policy-relevant estimates of their citizens’ population-level characteristics. In this chapter, we will explore this literature with an eye for investigating how an over-emphasis on self-identification can artificially inflate Métis population data for citizens of the Métis nation. Drawing on a conceptual case study, we will explore the current data situation of the Métis nation in Canada and suggest that compared to other Indigenous nations in other nation-states, Métis data sovereignty is limited to geographical regions with no national strategy, and thus is still largely reliant on existing and externally generated national census data.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.020 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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".