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Record W2011069356 · doi:10.1177/0008429814526144

Participation and Causality

2014· article· en· W2011069356 on OpenAlexvenueno aff
Gregory W. Dawes

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicReligious Studies and Spiritual Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMAGIC (telescope)Causality (physics)Citizen journalismSchema (genetic algorithms)EpistemologyDoctrinePsychologySocial psychologyDimension (graph theory)CognitionSociologyPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

A recurring debate within discussions of religion, science, and magic has to do with the existence of distinct modes of thought or “orientations” to the world. The thinker who initiated this debate, Lucien Lévy-Bruhl, distinguished two such orientations, one characterized as “participatory” and the other as “causal.” The present essay attempts to clarify what a participatory orientation might involve, making use of the social-psychological category of a “schema.” It argues that while the attitude to which Lévy-Bruhl refers is to be distinguished from an explicit body of doctrine, it does have a cognitive dimension and can embody causal claims. It follows that if such a distinction is to be made, it is not helpfully characterized as a contrast between participation and causality. A better distinction might be that between a mythical and an experimental attitude to the world.

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)0.021
metaresearch head score (Gemma)0.042
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 score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.042
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.033
Scholarly communication0.0060.015
Open science0.0020.008
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.174
GPT teacher head0.404
Teacher spread0.230 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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