Painting the ‘Essential’ Green Activist: Critical Interrogations of Responses to Environmental Activism
Bibliographic record
Abstract
In this paper, qualitative Directed Content Analysis is used to elucidate and analyze media rhetoric and legal rhetoric found in prominent news publications reporting on green protests in Canada and the United States. Preliminary theory suggested commodification of the environment encourages the denigration of green dissenters and may aim to lead to negative conceptualizations of the ‘green activist’ in the public consciousness. Further content analysis notions that the political leanings of given news publications may be the strongest predictor of the level of support/opposition to green protest that an article will purvey. And, animal advocacy, youth-led dissent, protest around critical infrastructure, and disruptive-to-civilian protest are suggested to be solid predictors for heightened negativity in coverage. Furthermore, protestors were rarely depicted as threats to peoples’ safety but more often to the established status quo of the treadmill of production.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".