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How does religious attendance shape trajectories of pornography use across adolescence?☆

2016· article· en· W2341921313 on OpenAlexafffund
Kyler R. Rasmussen, Alex Bierman

Bibliographic record

VenueJournal of Adolescence · 2016
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsTellabs (Canada)University of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPornographyReligiosityPsychologyAttendanceConsumption (sociology)Church attendanceDevelopmental psychologySocial psychologyPrayerMedia consumptionAdvertisingSociology

Abstract

fetched live from OpenAlex

Research increasingly calls attention to the possibility of detrimental consequences of pornography use among adolescents. However, few studies examine adolescent pornography consumption longitudinally or consistently examine the role of religion in shaping pornography consumption, despite an established theoretical basis for the moderating effects of religious attendance on pornography consumption. Using a national longitudinal survey that follows respondents from adolescence into young adulthood, we show that pornography use increases sharply with age, especially among boys. Pornography consumption is weaker at higher levels of religious attendance, particularly among boys, and religious attendance also weakens age-based increases in pornography consumption for both boys and girls. Overall, pornography use increases across adolescence into young adulthood, but immersion in a religious community can help weaken these increases. Future research should follow respondents across adulthood, as well as examine additional aspects of religiosity (e.g., types of religious belief or the regular practice of prayer).

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.323
Teacher spread0.292 · 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 designObservational
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

Citations69
Published2016
Admission routes2
Has abstractyes

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