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Record W1992701093 · doi:10.1163/15685276-12341240

Religious Studies as a Life Science

2012· article· en· W1992701093 on OpenAlexaff
Joseph Bulbulia, Edward Slingerland

Bibliographic record

VenueNumen · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScholarshipExpansiveHistory of religionsSociologyEpistemologyExpansionismDimension (graph theory)DualismSocial scienceReligious studiesLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Abstract Religious studies assumes that religions are naturally occurring phenomena, yet what has scholarship uncovered about this fascinating dimension of the human condition? The manifold reports that classical scholars of religion have gathered extend knowledge, but such knowledge differs from that of scientific scholarship. Classical religious studies scholarship is expansive, but it is not cumulative and progressive. Bucking the expansionist trend, however, there are a small but growing number of researchers who approach religion using the methods and models of the life sciences. We use the biologist’s distinction between “proximate” and “ultimate” explanations to review a sample of such research. While initial results in the biology of religion are promising, current limitations suggest the need for greater collaboration with classically trained scholars of religion. It might appear that scientists of religion and scholars of religion are strange bedfellows; however, progress in the scholarly study of religions rests on the extent to which members of each camp find a common intellectual fate.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.023
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.047
GPT teacher head0.401
Teacher spread0.354 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations36
Published2012
Admission routes1
Has abstractyes

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