Klimatförändringar. Hur klimat kommuniceras i svenska och nordamerikanska nyhetsmedier
Bibliographic record
Abstract
This study analyses the frames and discourses in different news media reporting on the same events in news outlets in Canada, the US, and Sweden. This was done by analysing both digital-born media and legacy media. The theoretical framework consists of theories about discourse, framing, media logics, the economic prerequisites for journalism, and environmental journalism. The aim is to find what frames, discourses, tone and what voices are being heard in the news coverage of Greta Thunberg’s climate protest, the migrant caravan, and the UN report on climate change released in 2018. Also, differences in the different media are analysed. This is done through discourse analysis by using Fairclough’s CDA and the three-dimensional model, combined with tools from critical linguistics. The analysis of the news texts found that the discourses in the coverage of the three events followed previous research on journalistic values, production and the way that climate change events were reported (or not reported) on. The study also found some themes, frames, that were producing new discourses in climate change journalism. Among these was the way that Greta Thunberg and other young voices were heard on a subject that previously has been heavily focused on politicians, scientists and NGO’s. Thunberg and the migrant caravan were also covered more extensively by the news media included than the UN report, not framing climate in the articles, even though they are about climate change events.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".