Bats in Folklore and Culture: A Review of Historical Perceptions around the World
Bibliographic record
Abstract
Belief systems of people have always been closely related to animals, which are symbolized in traditional narratives. Sociocultural definitions of animals as “good or evil” have persisted throughout the history of human beings. In the West, bats are often perceived as evil spirits, Vampires, and harbingers of death, while some cultures across the Asia-Pacific region associate bats with good fortune. Here, we review documented narratives and surveys from around the world and our ethnographic observations from Europe to analyze beliefs associated with bats. We explore the role that bats play in traditional narratives and the likely reasons for their salience, including their connections with the extraordinary and supernatural. Finally, we discuss shortly the need of education to change attitudes toward bats. In North America, education has had some effect as more people have started to understand how useful bats truly are and how few cases of bat-born rabies transmission to humans there have been in the United States and Canada. It remains to be seen, however, how effectively the further education efforts could halt or even reverse the decline of the bats around the world. It is also noted that bat tourism has a potential to conserve bat populations while providing social and economic benefits to local people in host communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".