The Challenges of Interrupting Climate Colonialism in Higher Education: Reflections on a University Climate Emergency Plan
Bibliographic record
Abstract
In this article Sharon Stein and Jan Hare ask how higher education institutions might begin to confront the connections between climate change and colonization. To grapple with this question, they examine the dynamics through which climate action can reproduce colonial relations and reflect on the challenges, complexities, and possibilities that emerged in the context of one university’s Indigenous engagement efforts around a climate emergency declaration. The authors suggest that if universities seek to interrupt climate colonialism, they will need to commit to upholding Indigenous rights, knowledges, and self-determination and to accepting responsibility for repairing colonial harm and developing respectful, reciprocal relationships with Indigenous communities and lands. To fulfill these commitments, universities will need to avoid the common tendency to seek quick solutions and instead support the development of institutional conditions and individual capacities that would make it possible to have difficult conversations about the historical and ongoing ways that they have been complicit in social and ecological harm.
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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 | 0.022 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".