Religion and climate change: varieties in viewpoints and practices
Bibliographic record
Abstract
Abstract Although religions are major social actors and institutions with considerable reach, relatively little social science research has focused specifically on the interaction of religious bodies and human‐induced climate change. Most of the current scholarship on the topic has been theological, pastoral, or normative, and specific to particular faiths; the focus of such scholarship is to draw on resources internal to the faith in order to make the case to adherents about the duty to attend to climate change. Only recently has empirical or social scientific research sought to examine what the world's religions and their adherents are actually saying or doing about climate change. Reviewing this research is the focus of this article. An essential first step is to conceptualize the problematic term ‘religion’ and to describe the extensive diversity of the world's religions. Religion includes beliefs, worldviews, practices, and institutions that cross borders, time, and scale from the level of individuals all the way to transnational and transhistorical movements. A summary of religious engagements with climate change is followed by two case studies that show the complexity of religion and religious engagement with climate change. The Pacific Islands are used as a geographic case. Buddhism is used as a case study of a specific faith tradition. Because the world's religions and faith groups are major social institutions and sites of collection action, greater attention to them by climate‐oriented social scientists is recommended. WIREs Clim Change 2014, 5:261–279. doi: 10.1002/wcc.268 This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Perceptions of Climate Change Social Status of Climate Change Knowledge > Climate Science and Social Movements
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".