Social and Political Convergence on Environmental Events: The Roles of Simplicity and Visuality in the BP Oil Spill
Bibliographic record
Abstract
Cet article étudie de quelle façon et à quel moment les journaux, les ONG environnementales, les entreprises privées et le gouvernement convergent autour des événements environnementaux. En utilisant les données sur le déversement de pétrole BP en 2010 tirées des journaux aux États‐Unis, au Canada et en Grande‐Bretagne et des communiqués de presses de Greenpeace, du Club Sierra, de Halliburton, de Transocean, d’Exxon/Mobil et les annonce de presse de la secrétaire de presse pour le Maison Blanche, nous étudions la capacité d'un événement à faire converger des actions sociales et politiques. En concevant les événements comme des actants, nous vérifions les arguments tirés des publications sur les mouvements sociaux et sur la définition de l'agenda politique à propos du timing, de la simplicité et de la visualité afin de comprendre comment les acteurs politiques convergent. Nous observons que l'effet de convergence est lié au timing, mais pas à la simplicité ou à la visualité. This paper examines how and when newspapers, environmental nongovernmental organizations, businesses, and the government converge on environmental events. Using data on the 2010 BP Oil Spill from newspaper articles in the United States, Canada, and the United Kingdom, press releases by Greenpeace and Sierra Club, press releases by BP, Halliburton, Transocean, ExxonMobil, and Shell, and press statements by the White House Press Secretary, we examine an event's potential to trigger convergence of social and political action. By treating events as political actants, we examine arguments from the agenda‐setting and social movement literatures on timing, simplicity, and visuality to understand when political actors converge. We find that convergence is related to temporal cycles but not simplicity or visuality.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".