MétaCan
Menu
Back to cohort
Record W2997468002 · doi:10.3138/jrpc.2017-0050

Prime Time for Prayer: An Analysis of Prayers Offered and Answered in the Reality Series<i>Answered Prayers</i>

2019· article· en· W2997468002 on OpenAlex
Sharon Lauricella

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Religion and Popular Culture · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPrayerPower (physics)Grounded theoryPrime timePsychologySociologySocial psychologyQualitative researchTheologySocial scienceAdvertisingPhilosophy

Abstract

fetched live from OpenAlex

Media power couple Roma Downey and Mark Burnett’s 2015 reality program Answered Prayers appeared as a six-episode series on TLC. The program depicts prayer lives through spoken interview-style vignettes and reenactments portraying individuals and families in crisis. This article addresses the ways in which Answered Prayers depicts how people pray, why they do so, and what “answered prayers” look like via reality media. A grounded theoretical analysis (Charmaz 2006) allows for themes and relationships in the data to emerge. Results indicate that this reality program suggests to viewers that prayers are always answerable. A model of relationships between offering prayers and receiving answers is presented, and the objectives of the producers of the program are addressed.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.264
Teacher spread0.242 · 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