The Role of Discrepancies Between Online Pornography Created Ideals and Actual Sexual Relationships in Heterosexual Men’s Sexual Satisfaction and Well-Being
Bibliographic record
Abstract
Contemporary sexually explicit Internet materials (SEIM) are commonly unrealistic. Following from self-discrepancy theory, we proposed that discrepancies between ideal and actual sexual experiences depicted in SEIM (ideal-actual sexual discrepancy; IASD) may be important in understanding the association between SEIM consumption, sexual satisfaction, and general well-being for heterosexual men. Participants from a general online community ( n = 195) were assessed via an online survey. Path analysis showed that the relationships between SEIM consumption and outcomes were not homogenous across age cohorts. While SEIM consumption and IASD contributed to sexual dissatisfaction for men in their 20s, only IASD had a direct relationship for men in their 30s. Higher IASD accounted for lower sexual satisfaction for men across age cohorts, suggesting that IASD may be a more stable factor as compared to quantity of consumption alone for explaining the negative association between SEIM consumption, sexual satisfaction, and all measured aspects of well-being.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".