Weathercaster Views on Informal Climate Education: Similarities and Differences According to Climate Change Attitudes
Bibliographic record
Abstract
Surveys have found that weathercaster views on climate change are diverse, with a large majority agreeing that climate change is happening but most remaining unconvinced that human activities are the principal cause. We hypothesized that these differences in climate change views could have implications for weathercasters acting as informal climate change educators, as well as for professional development training for weathercasters attempting to serve such roles. We asked weathercasters at a professional society meeting to provide brief statements on climate change and their roles to educate viewers about climate. We then pooled these statements for an online card-sort activity completed by 29 weathercasters and used network analysis to study the epistemologies of groups according to climate change attitudes. Despite different views on climate change, all weathercasters had a shared ethos for developing their climate change views through consulting observational data and multiple sources of information. Additionally, all weathercasters shared the concern that informal climate education focus on “the science and only the science.” Looking specifically at factual statements on climate change, all weathercasters classified the statement, “Climate is always changing,” as significant for informal climate education. However, there were differences in how weathercasters perceived the importance of changes in the atmospheric concentration of CO2 and how it relates to human activities. The implications of these findings are twofold. First, without interventions to empower all weathercasters as science communicators, the community may split into communicators explaining the contributions of human activities to climate change versus those who question it. Second, professional societies can play important roles to confront this schism through forums that address conflict, the science–policy interface, and scientific discussions around climate. By appealing to values and codes of conduct shared by all weathercasters, professional development activities can help them build confidence in making public statements about climate change as well as to develop appropriate conceptual scaffolding for relationships between human activities, greenhouse gas emissions, global warming, and 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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".