The morning after Canada’s Truth and Reconciliation Commission report: decolonisation through hybridity, ambivalence and alliance
Bibliographic record
Abstract
In Canada, 2015 will be remembered for the publication of the Truth and Reconciliation Commission Report which related to all Canadians the impacts of the Indian residential school system. The Commission invokes the United Nations Declaration on the Rights of Indigenous Peoples and uses the term reconciliation as a national strategy for moving forward. This paper employs an autoethnographic methodology and proposes that reconciliation might benefit by finding ways of confronting the Other within; I describe my reflections on a trip to the 2015 conference Learning at Intercultural Intersections at Thompson Rivers University. My social and cultural experiences as a Korean Canadian academic and administrator are challenged in order to consciously shift my own colonising mindset. Reconciliation in Canada will require significant personal, professional, institutional and sociocultural inquiry. What does it mean to discover the Other within? How do we walk with Indigenous peoples? How do educators come to be called ally by Indigenous peoples?
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.051 | 0.029 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".