Bibliographic record
Abstract
Martha Harroun Foster's study of Montana's multiracial Métis reveals that groups in the United States have long struggled for recognition of their aboriginal heritage. We Know Who We Are joins a growing body of literature that seeks to unravel the complexities of ethnic identity in plural societies, a highly emotional and controversial issue. Foster is particularly intrigued with how a group of people with Indian and European ancestry, which lacks formal organization and governmental sanction, and sterotypical Indian cultural traits, still sees itself as a distinct people. In a well-written, theoretically complex introduction, the author outlines the factors that affected the development and maintenance of Métis identity, an ethnicity that has been fluid, situational, inclusive, and adaptive. Borrowing from Fredrik Barth's groundbreaking 1969 study of ethnic boundaries, Foster finds that a complex mixture of economic activities, government policies, ascription by outsiders, and self-ascription enhanced Métis community persistence (“Introduction,” in Ethnic Groups and Boundaries, ed. Fredrik Barth, pp. 9–38). According to the author, however, the group's flexible kinship organization proved most central to the Montana band's survival since its genesis in the eighteenth-century Red River of the North region of the Canadian-United States borderlands.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.048 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".