Working the fringes: The role of letters to the editor in advancing non-standard media narratives about climate change
Bibliographic record
Abstract
This article examines the role of letters to the editor in advancing and sustaining non-standard narratives about climate change in the print media. The letters page is a unique section of the newspaper that is subject to distinct functional and normative pressures. It is also a place where standard media norms are weakest and non-journalistic narratives have an opportunity to leak in. Using research into climate change coverage in eight major Canadian dailies in 2007-2008, the article employs content analysis and critical discourse analysis to examine how letters advance fringe arguments into the print media landscape that would not stand up to regular journalistic scrutiny. While these arguments come from all sides of the issue, it is argued that letters are particularly important for establishing and legitimizing conservative-skeptical perspectives on climate change.
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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 | 0.030 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.030 | 0.021 |
| Scholarly communication | 0.030 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| 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 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".