Enduring Indigeneity: Community Consultation as a Process for Indigenizing Curriculum at a College in Ontario
Bibliographic record
Abstract
In 2015, the Truth and Reconciliation Commission (TRC) released its report which included 94 Calls to Action to address the legacy impacts of the Indian Residential School System in Canada. With education at the forefront of reconciliation, Call to Action #62 calls on post-secondary educators to integrate First Nations, Métis and Inuit content into their curriculum, to Indigenize teaching and learning within an education system built on Eurocolonial worldviews. A post-secondary institution located in southern Ontario (referred to by the pseudonym SCAAT) is making decolonization an institutional priority, especially as it is aligned with their Equity, Diversity and Inclusion (EDI) initiatives. Therefore, this Organizational Improvement Plan (OIP) aims to address the deficit of Indigenous worldviews represented across curriculum within the Faculty of Arts (FOA) at SCAAT through a process of Indigenization. Change agents will implement a consultation process with members of the local First Nation on whose traditional territory the college resides, so that curriculum reform for Indigenous education is informed by place-based stories, histories, knowledge and perspective; this underscores the objective of Indigenization. The author of this OIP identifies as Anishinaabe and the change is approached in an Indigenous wholistic framework, where it is pertinent that the writing privileges Indigenous perspectives, epistemologies, and methodologies. Through meaningful Indigenization, the FOA demonstrates a commitment to the authentic resurgence of Indigenous identity across curriculum offerings which will contribute to mutually respectful Indigenous-settler relations in support of reconciliation.
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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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.072 | 0.027 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".