Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".