Non‐Indigenous Canadians' Post‐Colonial Ideologies, Allyship and Collective Guilt Predict Support for Reconciliation, Collective Action and Political Tolerance
Bibliographic record
Abstract
ABSTRACT Since the release of the Canadian Truth and Reconciliation Commission's (2015) report and their 94 Calls to Action, there has been a push to advance truth and reconciliation with Indigenous peoples in Canada. Much of the heavy lifting has been done by Indigenous peoples; but to comprehensively redress injustices there is a need for non‐Indigenous support. In two studies with non‐Indigenous Canadians ( n = 355; n = 341), we investigated post‐colonial ideologies (historical negation, symbolic exclusion), ally/supporter identity and collective guilt as predictors of support for reconciliation and Indigenous collective action movements, and political tolerance of Indigenous peoples. Consistent with hypotheses, higher post‐colonial ideologies, lower ally/supporter identification and lower collective guilt related to less support and less political tolerance. Collective guilt emerged as a mediator for support for reconciliation and Indigenous collective action (except for symbolic exclusion in Study 1); but it moderated the relations for political tolerance. Collective guilt also moderated relations between symbolic exclusion and ally/supporter identity with support for reconciliation in Study 1. Future directions for advancing understanding of post‐colonial ideologies and possible applied interventions aimed at improving intergroup relations are discussed.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".