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Record W4205866436 · doi:10.3138/jrpc.2020-0027

Watching Movies in Jonestown: A Cultural Interlocutor Approach to Visual Media and New Religions

2022· article· en· W4205866436 on OpenAlexaffvenue
Kristian Klippenstein

Bibliographic record

VenueJournal of Religion and Popular Culture · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExtant taxonSociologyGrammarDoctrineVocabularySociocultural evolutionSocial mediaEpistemologyAestheticsMedia studiesLinguisticsArtAnthropologyPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

This article argues that new religious movements (NRMs) develop as cultural interlocutors. As emergent social bodies that respond to extant norms, structures, and values, NRMs can deploy cultural products as a shared vocabulary and grammar in their response to surrounding society. To demonstrate this approach’s ability to parse NRMs’ relations to popular culture while highlighting organizationally distinctive dimensions of such interactions, this article examines Jim Jones’s references to visual media shown in Jonestown in 1978. Jones critiqued movies and television as tools of social control, repurposed documentaries and films as evidence to support his proffered doctrine, and creatively presented movies as analogues of the commune’s perceived challenges. This threefold hermeneutic shaped the Peoples Temple’s beliefs and behavior, as well as its own media productions.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.012
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.333
Teacher spread0.306 · 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 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

Citations0
Published2022
Admission routes2
Has abstractyes

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