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Record W2593570975 · doi:10.24204/ejpr.v8i3.1690

Evidentially Compelling Religious Experiences and the Moral Status of Naturalism

2016· article· en· W2593570975 on OpenAlexaff
Travis Dumsday

Bibliographic record

VenueEuropean Journal for Philosophy of Religion · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTheology and Philosophy of Evil
Canadian institutionsConcordia University of Edmonton
Fundersnot available
KeywordsMetaphysicsNaturalismPhilosophyIrrational numberEpistemologyVisionJudgementFalsityNegationNatural (archaeology)Variety (cybernetics)TheologyHistoryLinguistics

Abstract

fetched live from OpenAlex

Religious experiences come in a variety of types, leading to multiple taxonomies. One sort that has not received much attention as a distinct topic is what I will call ‘evidentially compelling religious experience’ (ECRE). The nature of an ECRE is such that if it actually occurs, its occurrence plausibly entails the falsity of metaphysical naturalism. Examples of ECREs might include visions / auditions / near-death experiences conveying information the hearer could not have known through natural means, later verified; unambiguously miraculous healings; fulfilled prophecy; supernatural rescues; inter-subjective religious experiences (e.g., multiple people simultaneously having the same vision of the Virgin Mary), etc. After presenting a representative set of published case studies of ECREs, I argue that for most settled metaphysical naturalists (though not all), the combination of a settled metaphysical naturalism with an awareness of the relative commonality of testimony to ECREs is either irrational or immoral. This is because that conjunction entails either an unjust and uncharitable judgement on a great many of those testifying to ECREs (namely that they are liars), or an irrational refusal to acknowledge this entailment.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.249
Teacher spread0.209 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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