Bibliographic record
Abstract
For the past six years I have beell living ancl working in northern Manitoba. teaching in the college and uiliversity environment. The majo~ity of students x e Abo~iginal, and the majority of the courses I teach x e in the asea ofAbo~iginal ~ t u d i e s . ~ As a non-Aboriginal newcomer to the north, I a111 keenly awase of the need for my approach and my work: to be relevant to students and to the larger community. Education. however. has not often served the people of the i~orth very well. It has often been a tool of and agent for assiinilationist practices by church and state. The residential school era which saw thousands of Aboiigiilal children tnl;en from fainily and con~inunity to l ean western ways and values in an alien setting begail in the late nineteenth century aild continued 011 illto the 1960s. The effects x e still being felt today. Eclucation. then. has been a force of fragmentation and dislocatioil POImany individuals, families and co111111~11ities.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.057 | 0.015 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".