Settler-colonial geographical ignorance in Canadian education
Bibliographic record
Abstract
Despite increasing attention to Indigenous demands for justice, self-governance and the decolonization of Canadian society, many Canadians remain deeply unaware of the complex ways Indigenous and non-Indigenous lives entwine in Canada and of the past and present settler-colonial structures which continue to control and harm Indigenous Peoples and lands. Drawing on our decade-long project examining education at multiple levels in multiple jurisdictions and bringing together scholarship on settler-colonial ignorance, decolonizing education and geographical imaginaries, we highlight how pervasive settler-colonial geographical ignorance, (re)produced through formal education, inhibits many Canadians’ capacities to understand themselves as inextricably linked and responsible to Indigenous Peoples. Through our examination of the results of surveys of college and university students and of public kindergarten to Grade 12 curricula in three Canadian provinces, we provide analyses of settler-colonial forms of geographical unknowing (re)produced in Canadian public education and echoed in the discourses of students. Our analysis draws out commonly held (mis)perceptions and prejudicial attitudes that pervade settler-colonial imaginations, allowing us to identify the entangled temporal, spatial and (non)relational dimensions of settler-colonial geographical ignorance in Canada. Considering the ways that many non-Indigenous people misunderstand and ignore the geographies of settler-colonialism and of Indigenous Peoples, we hope to contribute to ongoing, urgent investigations into the ways that settler-colonial and geographical ignorance serve to oppress Indigenous Peoples and exploit the lands to which they belong for others’ benefit. Furthermore, by focusing on and demonstrating the spatial nature of such ignorance, we argue that (re)conciliation between Indigenous and non-Indigenous Peoples in Canada must also be spatial.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.029 | 0.015 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".