Lessons in relationality: reconsidering the history of education in North America
Bibliographic record
Abstract
This article offers a sampling and critique of the history of education in North America, including Canada, the United States and Mexico. Being Black and Indigenous academics, respectively, the authors’ scholarship centres on community relationships, considering activism around #BlackLivesMatter and Indigenous Peoples, especially with the news of thousands of unmarked graves at former Indian Residential Schools in Canada. Amidst increasing global calls for decolonisation, social justice and accountability, we ask: how should one consider the history of education in North America amidst social unrest, climate change, the SARS-CoV-2 pandemic, ongoing colonialisms, gender inequities, police violence against Black bodies and unmarked graves of Indigenous children? This paper traces histories of Indian Residential Schools, explores schooling structures and emerging settler states, and examines the growing focus on local histories to offer new directions in the history of education that challenge antiquated national narratives.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.064 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.008 |
| 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".