MétaCan
Menu
Back to cohort

Religion

2015· other· en· W4252022397 on OpenAlexfundno aff
Benjamin Grant Purzycki, Jordan Kiper, John H. Shaver, Daniel Finkel, Richard Sosis

Bibliographic record

VenueEmerging Trends in the Social and Behavioral Sciences · 2015
Typeother
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
FundersEconomic and Social Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsSocialitySociologyVariety (cybernetics)Representation (politics)CognitionMythologyEthnographyEpistemologyPhenomenonCognitive science of religionPsychologyAnthropologyPoliticsEcologyPolitical scienceHistoryComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract Religions are complex systems that can adapt to diverse environments because of the dynamic relationship of their internal parts. The most fundamental of these parts includes supernatural beliefs, rituals, and myths. The social scientific study of religion focuses on these parts and builds on previous generations of research to provide distal explanations for religion as a dynamic phenomenon. In recent years, interest in the social science of religion has turned to the cognitive and behavioral studies of religion. The cognitive science of religion documents the mental organization and structure of religious thought, while the behavioral science of religion focuses on ritual behavior as the building block of sociality. Key issues for future research include the ontogeny of religion, the cognitive and cross‐cultural representation of religious concepts, the relationship between religion and reproduction, and the evolution of religion. With these new frontiers have come a variety of novel methodologies but also an emphasis on the need for comparative ethnography.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.103
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.129
GPT teacher head0.470
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEmerging Trends in the Social and Behavioral SciencesSame topicReligion and Society InteractionsFrench-language works237,207