The politics of politicization: Climate change debates in Canadian print media
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
Politicization is frequently employed as an analytic concept to explain the relationships between politics and media coverage of climate change. However, relatively few works explore how different notions of politicization are mobilized by actors in media discourses themselves. This article does so via a framing analysis of climate change coverage in Canadian newspapers. I investigate how different relationships between science and politics are conceived and associated with varying positions on climate change. In particular, I examine a supposition in science and technology studies that the media remains committed to deficit models and thus uncritically reproduces the authority of science. Scientistic discourses exist but among a diversity of politicization framings. A key finding is that the strongest appeals to scientific neutrality are associated with climate skepticism. This casts light on the nuanced, strategic "politics of politicization" in climate change debates. A more fine-grained and reflexive approach to politicization discourses can help identify productive interventions.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | medium |
| gpt | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | medium |
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it