Fossil fuel industry influence in higher education: A review and a research agenda
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The evolution of fossil fuel industry tactics for obstructing climate action, from outright denial of climate change to more subtle techniques of delay, is under growing scrutiny. One key site of ongoing climate obstructionism identified by researchers, journalists, and advocates is higher education. Scholars have exhaustively documented how industry‐sponsored academic research tends to bias scholarship in favor of tobacco, pharmaceutical, food, sugar, lead, and other industries, but the contemporary influence of fossil fuel interests on higher education has received relatively little academic attention. We report the first literature review of academic and civil society investigations into fossil fuel industry ties to higher education in the United States, United Kingdom, Canada, and Australia. We find that universities are an established yet under‐researched vehicle of climate obstruction by the fossil fuel industry, and that universities' lack of transparency about their partnerships with this industry poses a challenge to empirical research. We propose a research agenda of topical and methodological directions for future analyses of the prevalence and consequences of fossil fuel industry–university partnerships, and responses to them. This article is categorized under: Social Status of Climate Change Knowledge > Climate Science and Decision Making Climate, Nature, and Ethics > Ethics and Climate Change Social Status of Climate Change Knowledge > Sociology/Anthropology of Climate Knowledge Social Status of Climate Change Knowledge > Climate Science and Social Movements
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it