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Record W2596601711 · doi:10.31581/jbs-25.1-2.4(2015)

Seven Narratives of Religion

2015· article· en· W2596601711 on OpenAlexvenueno aff
Benjamin Schewel

Bibliographic record

VenueThe Journal of Bahá’í Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeSecularizationTypologyConstruct (python library)Narrative inquirySociologyEpistemologyAestheticsLiteraturePhilosophyReligious studiesAnthropologyArt

Abstract

fetched live from OpenAlex

The purpose of this article is to explore how the contemporary academic discourse on religion is, on the whole, beginning to resonate with the broader vision of religion provided by the Bahá’í Writings. Toward this end, I argue that the contemporary academic discourse on religion pivots around seven narrative frameworks, which I describe respectively as the (1) subtraction, (2) renewal, (3) transsecular, (4) postnaturalist, (5) construct, (6) perennial, and (7) developmental narratives. Each of the narratives offers unique insights into the historical evolution of religion and the changing place of religion in the modern world, many of which align with the Bahá’í teachings. I endeavor to substantiate this claim in three steps. First, I discuss the theory of secularization and the nature of its recent disruption in order to elucidate the narrative problematic that lies at the heart of the contemporary academic discourse on religion. Second, I analyze the seven narrative frameworks and show how each resonates with certain aspects of Bahá’í teachings. And third, I conclude by considering how my typology of seven narratives could be used to frame further inquiry.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.114
GPT teacher head0.429
Teacher spread0.315 · 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 designQualitative
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

Citations2
Published2015
Admission routes1
Has abstractyes

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