The Ethical and Ecological Limits of Sustainability: A Decolonial Approach to Climate Change in Higher Education
Bibliographic record
Abstract
Abstract In this article, I offer a decolonial critique of the ethical and ecological limits of mainstream sustainability efforts in higher education. In doing so, I identify colonialism as the primary cause of climate change, and the primary condition of possibility for modern higher education. I further suggest that the abiding failure to address the centrality of colonialism in both climate change and higher education is not a problem of ignorance that can be solved with more information, but rather a problem of denial that is rooted in enduring investments in the continuity of existing institutions and a modern-colonial ‘habit-of-being’ (Shotwell, 2016). I argue that in order to face the ethical and ecological impossibilities of making higher education institutions sustainable, we will need to set our horizons of hope beyond the promises that they offer.
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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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.123 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.015 |
| 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".