An Arctic encounter with Indigenous and non-Indigenous youth as pedagogy for historical consciousness and decolonizing
Bibliographic record
Abstract
In this article I reflect on a pedagogical encounter that occurred during my research with a program called Students on Ice, a ship-based expedition to the Arctic with youth and adults, including a large number of Indigenous Northerners. Together, we visited a National Historic Site and confronted part of Canada’s history of colonization. I frame this powerful pedagogical encounter with Dwayne Donald’s (2012) theory of decolonizing education, wherein processes of decolonizing and historical consciousness are deeply linked. I work to identify the dimensions of this encounter that produced such a powerful learning opportunity in service of both historical consciousness and decolonizing. I found that as students learned how people are differently historically conditioned, they did not resort to voyeuristic distance, but rather recognition of connection, and from that, “ethical relationality” (Donald, 2012) may flow.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.027 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.002 | 0.006 |
| 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".