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Record W2796302128 · doi:10.1177/193979091500800106

A Theology of the Body for a Pornographic Age

2015· article· en· W2796302128 on OpenAlexaff
Rob Rhea, Rick Langer

Bibliographic record

VenueJournal of Spiritual Formation and Soul Care · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsHuman sexualityContext (archaeology)Formative assessmentSoulPornographyThe InternetPsychologySocial psychologySociologyEpistemologyGender studiesComputer scienceWorld Wide WebPsychoanalysisHistoryPedagogy

Abstract

fetched live from OpenAlex

The Internet has become a normal and formative influence in the lives of emerging adults. Within this engagement, the consumption of sexualized content has become de rigueur. The regular use of pornographic materials has raised fundamental questions regarding online encounters vis-à-vis real encounters. Is an online engagement of sexually explicit materials simply a “virtual” experience or does it necessarily have a physical dimension? How are cyber-sexual encounters the same or different than physical ones? These issues call for an understanding of the body and sexuality that extends into the cyber-based versions of the self. Spiritual formation efforts will increasingly need to take into account the online lives and interactions of people. To that end, understanding the interaction of the body and soul, when engaging an online sexually explicit image, is an important task of the church. This article will lay the groundwork for a biblical understanding of being human and being sexual within an online context. The goodness of the body will be addressed as well as an exploration of the ways sin affects the whole person, particularly through the engagement of pornography. Together, this discussion will better equip the church to continue to assist Christians in conforming their lives, online or offline, to the image of Christ.

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)0.000
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 score0.391
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.055
GPT teacher head0.268
Teacher spread0.213 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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