Canadian Social Economy Hub With Foreword and Edited by Janel Smith
Bibliographic record
Abstract
1 While Indigenous people have struggled to overcome the legacy of colonialism in Canada, Settler governments have struggled with their own past, and ongoing role in the colonial project. What to do about the “Indian Problem ” is a persistent question that remains unsatisfactorily answered. Early treaties between Indigenous peoples and Settlers invoked the spirit of the Two Row Wampum, and a respect for peaceful co-existence through noninterference. This spirit of noninterference remained constant in Indigenous rhetoric through till the latter half of the twentieth century. Since 1991, however, the discourse of Indigenous-Settler Relations has taken a dramatic shift away from respect for distinctiveness towards the language of neoliberalism. Evidence of this shift in discourse can be found in the reports of the Royal Commission on Aboriginal Peoples, The Harvard Project on American Indian Economic Development, and the Senate Standing Committee on Aboriginal Peoples. Recurring crises in Indigenous-Settler relations have often been followed by years of co-opting processes to the extent that certain Indigenous leaders are now increasingly acting upon and advocating for the neoliberal
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.024 |
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".