Towards a socio-cognitive orientation to religious text: a case study in Indian epic literature
Bibliographic record
Abstract
Religious Narrative, Cognition and Culture contains contributions dealing with religious narrative and cognitive theory written by some of the world’s leading scholars in the fields of cognitive science, narratology and comparative religion. At the heart of the volume are five papers which serve as sequels to each other. The first paper by the American biologist and semiotician Terrence W. Deacon explores the neurological processes and possible genetic foundations of how language emerged in Homo sapiens. This is followed nicely by the Canadian evolutionary psychologist Merlin Donald’s contribution which describes the possible phylogenetic routes in the development of language and culture. His bio-cultural approach is a major theme in the book. The third paper by the British psychologist Chris Sinha brings us to the bridge between neurological and communicative levels. In it he describes the complex interrelations between the ontogenesis and the sociogenesis of cognitive processes and demonstrates how they relate to reason, representation, figuration and imagination. The fourth contribution brings us to the level of narrative. It is by the Indian narratologist Rukmini Bhaya Nair in which she argues for a combination of neurology, narratology and a reworked speech-act approach that focuses on narrative rather than simply sentences. The final keynote is by the Finnish cognitive scientist of religion Ilkka Pyysiäinen. He brings us full round to religious behavior by showing how the psychology of ritual helps make narrative beliefs possible. These five contributions are followed by papers from Danish, Finnish, Icelandic and American scholars of religion covering religious narratives and emotional communication, gossip as religious narrative and area studies of religious narrative and cognition in the Old Testament, the New Testament, the Georgian Orthodox Church, Indian Epic literature, Australian Aboriginal mythology and ritual, and modern religious forms such as New Age, Asatro, astrological narrative and virtual rituals in 3D cyberspace.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".