Bibliographic record
Abstract
This important edited work is a critical step toward enlarging understanding of the identity, experience, and long history of the Métis, a people of Indian and European descent. While the Métis are officially recognized as an indigenous people in Canada, their story has been widely neglected there and in the United States. This collaborative effort, honoring the scholars Jennifer S. H. Brown and Jacqueline Peterson, and the Métis author Maria Campbell, continues their work of bringing renewed interest to this field. Contours of a People begins with a forward by Campbell that sensitively portrays her experience growing up Métis. It sets the stage for the other essays with a call for the exploration of Métis cultural and historical richness, especially by including a Métis perspective in the telling. Though there is much more to be done and many more stories to be told, this volume is a critical contribution that reaches out to Métis who would tell their stories and to those who would insist that the Métis experience not be neglected in the telling of U.S. and Canadian histories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.023 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".