A systematic review of changes in sexual attractions
Bibliographic record
Abstract
Does sexual attraction to specific targets change over the lifetime? This study consisted of a systematic review and narrative synthesis of longitudinal studies published before 2022 to examine this question. A novel definition of sexual attraction was drafted to guide our search: an orienting response to a stimulus (persons, attributes, contexts, acts, etc.) that generates sexual states (e.g., sexual arousal, fantasy, or interest). Studies published in English or French that reported empirical, longitudinal, and prospective data on sexual attraction were included. Of 5,475 potential studies identified, 24 met the inclusion criteria for analyses (15 independent samples of 11,943 participants). Each study was coded for descriptive statistics, definitions and measures of sexual attraction used, the period between assessments, and the number of participants who experienced any change in sexual attraction. All the included studies exclusively measured gender-based attractions; no studies assessed other targets of sexual attraction. Researchers typically did not define sexual attraction in their articles and, when they did, offered diverse definitions and conceptualizations. The Kinsey scale was the most frequently used measure of sexual attraction. In a pooled sample of 8,008 participants, 18% experienced some change in self-reported sexual attractions over a median period of approximately 20 months. These findings have implications for future research, highlighting the need for a clear definition and better measurement of sexual attraction.
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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 | 0.011 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".