Repairing Activist-Academic Relationships: Defining Methods to Improve Reciprocity and Movement Building in Degrowth
Bibliographic record
Abstract
The degrowth movement, advocating for an eco-socialist restructuring of world economies, has failed to find a political foothold in American politics. This is despite growing support in Europe and positive, yet limited, reception in Canada. Previous literature diagnoses the American degrowth movement with confused and ineffective rhetoric, inhospitable intramovement politics, and too little scholarly support. In this article, I argue differently. I focus on the relationships between academics and activists within American degrowth, understanding academic-activist relationships to be historically extractive but also generative and didactic. Using semistructured interviews with academics and activists, and discourse analysis of the press coverage of degrowth, I define the state of academic-activist relationships as severely underdeveloped and uncooperative. Finally, I find that significant reforms to higher education’s opacity, exclusivity, and extractive productivity, and that encouraging activists to proactively center their narratives in the movement, may improve the lax reciprocity and slow movement building of American degrowth.
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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 | 0.045 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".