A Research Agenda for Affective Dimensions in Climate Change Risk Perception and Risk Communication
Bibliographic record
Abstract
There is a growing body of literature that examines the role of affect and emotions in climate change risk perception and risk communication. Conceptions of affect and emotions have differed according to theoretical perspectives and disciplinary orientations (e.g., sociology of risk, psychology of risk, climate science communication), but little has been done to map these differences. This perspective article provides an in-depth analysis of the study of affect and emotions in climate change risk research through a literature review of studies published in the last 20 years. In this perspective, we examined how affect is conceived, what emotions have been considered, and their role in climate change risk perception and risk communication. Early studies in climate risk perception and risk communication included vaguely defined emotions (e.g., negative and positive) in climate risk perception and risk communication studies, more recently turning attention to how different affective dimensions interact with other factors, such as personal experience, knowledge, culture and worldviews, gender, and social norms. Using this review as a mapping exercise of the research landscape on affect and emotions in climate risk perception and communication, we suggest that future research could benefit from more interdisciplinary work that explores the role of different affective responses and their intensities before, during, and after climate-related 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".