Media Coverage and Perceived Policy Influence of Environmental Actors: Good Strategy or Pyrrhic Victory?
Bibliographic record
Abstract
In this article we analyze how media coverage for environmental actors (individual environmental activists and environmental movement organizations) is associated with their perceived policy influence in Canadian climate change policy networks. We conceptualize media coverage as the total number of media mentions an actor received in Canada’s two main national newspapers—the <em>Globe and Mail</em> and <em>National Post</em>. We conceptualize perceived policy influence as the total number of times an actor was nominated by other actors in a policy network as being perceived to be influential in domestic climate change policy making in Canada. Literature from the field of social movements, agenda setting, and policy networks suggests that environmental actors who garner more media coverage should be perceived as more influential in policy networks than actors who garner less coverage. We assess support for this main hypothesis in two ways. First, we analyze how actor attributes (such as the type of actor) are associated with the amount of media coverage an actor receives. Second, we evaluate whether being an environmental actor shapes the association between media coverage and perceived policy influence. We find a negative association between media coverage and perceived policy influence for individual activists, but not for environmental movement organizations. This case raises fundamental theoretical questions about the nature of relations between media and policy spheres, and the efficacy of media for signaling and mobilizing policy influence.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".