Bibliographic record
Abstract
Below are some basic terms necessary to understand any discussion of Indigenous people in Canada.Although formal and legal documents use the term "Aboriginal," in this book I use the term "Indigenous" in many circumstances because it is more acceptable to Indigenous people in Canada (Younging 2018). Aboriginal Peoples:The descendants of the original inhabitants of North America.The Canadian Constitution recognizes three groups of Aboriginal Peoples: Indians, Métis, and Inuit.These three distinct groups have unique heritages, languages, cultural practices, and spiritual beliefs.Aboriginal Rights: Rights that some Indigenous Peoples of Canada hold because of their ancestors' long-standing use and occupancy of the land.The rights of certain Indigenous Peoples to hunt, trap, and fish on ancestral lands are examples of Aboriginal Rights.These rights vary from group to group depending on the customs, practices, and traditions that have formed their distinctive cultures.Aboriginal self-government: Governments designed, established, and administered by Indigenous Peoples.Aboriginal Title: A legal term that recognizes an Indigenous interest in the land.It is based upon the long-standing use and occupancy of the land by today's Indigenous Peoples as the descendants of the original inhabitants of Canada.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.089 | 0.048 |
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".