The role of college and university faculty in the fossil fuel divestment movement
Bibliographic record
Abstract
Colleges and universities have played a critical role in the growing social movement to divest institutional endowments from fossil fuels. While campus activism on fossil fuel divestment has been driven largely by students and alumni, faculty are also advocating to their administrators for institutional divestment from fossil fuels. This article characterizes the role of faculty by reviewing signatories to publicly available letters that endorse fossil fuel divestment. Analysis of 30 letters to administrators signed by faculty at campuses throughout the United States and Canada reveals support for divestment from 4550 faculty across all major fields of inquiry and scholarship, and all types of faculty positions. Of these signers, more than 225 have specific expertise in climate change or energy. An in-depth analysis of 18 of these letters shows that a significantly greater proportion of tenured faculty sign open letters of support for divestment than do not-yet-tenured tenure-track faculty (15.4% versus 10.7%), perhaps reflecting concerns among not-yet-tenured faculty that such support might jeopardize their career advancement. This analysis suggests that faculty support for the divestment movement is more widespread than commonly recognized; this movement is more mainstream, and broader-based, than is often recognized. Revealing the scope and scale of faculty support for fossil fuel divestment may encourage additional faculty to engage, support and endorse this growing social movement that highlights the social impact of investment decisions, and calls upon colleges and universities to align their investment practices with their academic missions and values.
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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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".