In Pursuit of Truth: Challenging Colonial Narratives in Canadian Legislation with wâhkôhtowin and Other Indigenous Perspectives
Bibliographic record
Abstract
Nationwide events that gained global attention have prompted the Canadian government to engage in reconciliatory efforts to promote the revitalization of Indigenous languages. The resultant Indigenous Languages Act appears to address the issues that have been highlighted in the media over the past several decades. The discourse and rhetoric surrounding the Indigenous Languages Act suggest that the government has implemented legislation that effectively recognizes and reconciles past injustices towards Indigenous peoples. I argue that this oversimplifies the colonial-Indigenous relationship, glosses over the reasons why Indigenous languages are endangered in the first place, and presents only one side of the story. The methods I used to explore my concerns consisted of close readings and discourse analysis of past legislation and events that flowed from these laws. Indigenous methodologies and theorists guided my research, and I drew from Indigenous voices broadly and the Cree worldview of wâhkôhtowin specifically to provide Indigenous perspectives. My research found that legislation and other colonial constructs use possessive logics to maintain the status quo and benefit white patriarchal sovereignty, which is rarely beneficial to Indigenous peoples. I have shown that the missing pieces of Canadian history lie in wâhkôhtowin and the voices of Indigenous peoples, who provide the rest of the story, challenge colonial narratives, and amend history with the truth. Because discourse shapes reality, the consequence of this strictly colonial narrative is the continued dis-representation of history that ignores the lived experiences of Indigenous peoples and leaves mainstream society unaware of the true history of Canada. Despite federal claims of redress, my research found that the Indigenous Languages Act falls short of reconciliation and that only structural change will begin to address the loss of Indigenous languages. Meaningful reconciliation begins with engaging Indigenous perspectives and embracing cultural cornerstones such as wâhkôhtowin.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.092 | 0.066 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".