Practising an Anti-Colonial Citizenship Education Through a Blended Learning Course on Aboriginal Law
Bibliographic record
Abstract
In the wake of the Truth and Reconciliation Commission, Indigenous peoples and non-Indigenous Canadians find themselves aspiring towards transitional justice. Yet they do so with a democracy in need of some repair. One prime site for fostering democratic renewal – the post-secondary sector – is under pressure from corporatization and political forces working to narrow freedom of expression and academic freedom. This sector, however, continues to offer some hope through liberal, anti-oppressive, anti-colonial, and Indigenous pedagogies that promote a public ethical responsibility beyond the self. Yet encouraging these pedagogies is not straightforward, including for those teaching courses such as Aboriginal law in a blended learning format. In the context of the spread of online education and the dearth of scholarship on anti-oppressive pedagogies therein, on the one hand, and the reluctance of legal educators to adopt anti-colonial pedagogies, on the other, there is an urgency to build knowledge about how to develop citizenship education. Anti-colonial citizenship education includes content about the establishment of settler society and the status of Indigenous nations. Furthermore, it is operationalized through active learning practices. Based on Indigenous and non-Indigenous pedagogical theories, these practices are argued to support a tripartite “intellectual framework” comprised of critical thinking, collaboration, and self-directed learning. Through a case study of an undergraduate course, the argument is made for the efficacy of a number of active learning practices to produce this intellectual framework. It is suggested that, in addition to better learning outcomes, an anti-colonial citizenship education is materialized insofar as the intellectual framework inspires a sensibility for complexity and independent thinking, “civic culture,” and autonomous inquiry and openness to alternative epistemologies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".