Toward equality: Including non-human animals in studies of lived religion and nonreligion
Bibliographic record
Abstract
This article explores how sociologists of religion can respond to 'the animal turn' in studies of lived religion and nonreligion. We begin by considering how sociology has neglected the place of non-human animals and the 'more than human' in social life. We then turn to the sociology of religion, where animals have often been devalued or ignored as irrelevant to understanding religion in society. We argue that it is necessary to consider the ways in which human activities are shaped by non-human animals. This does not mean that animals should be thought of as nonreligious or religious. We contend that the failure to incorporate non-human animals in sociological considerations of religion and nonreligion replicates a hierarchical model, which sees human life as above or higher than non-human life and calls our attention to the place of sociological research amid the climate crisis.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.054 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| 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".