Reconciliation: An Emerging Type of Ignorance Amongst Settlers in Ontario
Bibliographic record
Abstract
This research project was conducted to critically analyze Ontario’s newest version of the Native Studies 1999/2000 courses - the Ontario Curriculum, Grades 9 to 12: First Nations, Métis, and Inuit Studies, 2019. Ontario’s curricula have previously omitted and misrepresented Indigenous peoples, and their historical and contemporary realities. Through a conceptual framework of ignorance, the study investigated the developmental process of the curriculum, and its content to understand how the curriculum will educate Ontario’s student population. The data was collected through a thematic analysis of the Ontario Curriculum, Grades 9 to 12: First Nations, Métis, and Inuit Studies, 2019 document, and of supporting media articles. The research project’s findings suggest a new emerging type of ignorance among settlers regarding the concept of reconciliation. The findings demonstrate that an oversimplified conceptualization of reconciliation is at the base of the new emerging type of ignorance. Reconciliation is simplified to renewing relationships between Indigenous peoples and settlers, while disassociating reconciliation from settler colonialism and critiques. Based on Wolfe’s (2006) logic of elimination, I theorize the presence of the new emerging type of ignorance regarding reconciliation is motivated to erase settler colonialism in the contemporary world. Finally, the research project concludes with recommendations for curriculum development and future research. Keywords: Indigenous peoples, settlers, Ontario, education, curriculum, ignorance, 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".