Communicating the environment: Guest editors’ introduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The articles gathered together in this special issue were submitted in response to a call for manuscripts, issued in 2009, on ‘Communicating the environment’. While the recent decade has seen the rise to dominance of ‘climate change’ as a focus for media, public and political environmental concern, as well as for science/social science research on the environment, the call for papers deliberately aimed more broadly at attracting contributions from the wider field of social science, media, communication and cultural studies research on environmental communication. The articles brought together here thus represent a rich and exciting range of research foci and, equally important in our view, of theoretical frameworks and research approaches to the study of environmental mediation and communication. Comprising a range of different national and media foci, they offer analyses of a diverse range of media forms including film/animation, television, promotional videos, newspapers and magazines, and with contributions by scholars from New Zealand, Canada, the US, the UK, Belgium, Denmark and Germany. The environmental issues examined range from climate change, nuclear power and agricultural biotechnology, to media portrayals of ‘nature’ and ‘environment’. Not surprisingly, given the rise of ‘framing analysis’ in the last two decades, several of the articles draw on, deploy and advance ‘framing analysis’, while often combining the insights from theories of ‘framing’ with content analysis and discourse analytical approaches. In our view, a particular strength of this special issue is
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it