Bibliographic record
Abstract
The largest school division in Winnipeg, Canada—the Winnipeg School Division—is undertaking several initiatives in the teaching for reconciliation and in meeting the educational mandate of the Truth and Reconciliation Commission of Canada’s 94 Calls to Action. These initiatives are being implemented in many of the division’s K-12 schools and a variety of subject areas. This articleexamines the reconciliatory initiatives that provide Indigenous and non-Indigenous learners alike with meaningful information about traditional practices and opportunities to engage in relationshipbuilding and cross-cultural understanding. The literature review section examines the historical and societal injustices perpetrated upon Indigenous peoples, newcomers’ needs around Indigenous issues, and the important role that Indigenous and non-Indigenous teachers have in the reconciliation process. The methodology section focuses on document analysis and its relevance as a research method. The article concludes with an examination of the potential and resistance of teaching for reconciliation in 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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.030 | 0.014 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".