Bibliographic record
Abstract
This chapter builds on the authors’ previous critiques of standard reductionist or conflict-orientated issues framing in the measurement of publics’ attitudes towards evolutionary science that can lead to overestimations of evolution rejection. Through the development of new and more sophisticated approaches to cross-cultural surveys, more nuanced drivers of global publics’ attitudes towards evolutionary science, including humans’ origins, have emerged. These approaches have evidenced that the rejection of evolutionary science is not a necessary component of religious belief in the UK, Canada, and the US, confirming the sometimes surprising social complexities around questions of human origins for both religious and non-religious groups. Since this initial research was undertaken, there has been a revisiting of the baseline assumptions and implicit biases in surveys around evolutionary science. However, the majority of these newer studies have remained focussed on North American and UK populations, leaving much of the world understudied. This chapter utilises new international survey data from Argentina, Australia, Canada, Germany, Spain, the UK, and the USA focussed on publics’ perceptions and lived experience of the relationships between science, religion, and evolution. This new research not only undertakes research across differing cultural contexts, it expands upon previous studies and deploys more sophisticated measures regarding attitudes around evolutionary science. Importantly, we identify not only evolution rejection by individuals within populations but also processes of social projection – whereby individuals expect to find evolution rejection within their own or others’ social groups. This allows the measurement not only of which sections of the population have concerns about evolutionary science but indicates how wider the social and cultural narratives surrounding evolutionary science might lead individuals or groups to perceive their social identity as being in conflict with evolutionary science endorsement. Finally, we discuss the results of measures that place evolution rejection within the context of the rejection of other science consensus positions, including anthropogenic climate change, vaccine safety, and the spherical nature of the earth.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.038 |
| Scholarly communication | 0.027 | 0.031 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".