Education as a Petro-Pipeline: Beyond the Limits of Education Research in the Face of Climate Change
Bibliographic record
Abstract
Considering the key cause of climate-harming carbon emissions is the increased use of fossil fuels, we might expect research in education to engage in petrocriticism—a critical way of reading the world that deconstructs how fossil-fuelled cultural expectations and practices, or “petroculture,” functions in education. To trace the intersection of fossil fuels and education, this article conducts a systematic literature review of both existing and emerging scholarship, engaging in a petrocritical reading of research themes to reveal the extent to which petroculture is naturalized and/or confronted. By examining both dominant research patterns and the notable silences, we conclude by making recommendations for how education scholarship can respond to climate science and contribute to a more livable future through research that takes up (a) petrocriticism, (b) mitigation and decarbonization, and (c) transformation toward alternatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".