Reasons Lesbian and Bisexual Adolescent Girls Have or Might Have Sex with Females or Males: Implications for Discordance between Sexual Identity and Behaviors and for Prevention of Pregnancy and STIs
Bibliographic record
Abstract
We examined reasons lesbian and bisexual adolescent girls have sex or, if sexually inexperienced, might have sex with girls or boys, and the role of internalized homonegativity in these relations and among lesbians. Girls were recruited online and classified as lesbian (n = 129) or bisexual (n = 193); the classification was validated. Love and pleasure were common reasons for having sex with girls, although more lesbian girls (LG) than bisexual girls (BG) endorsed love. BG, relative to LG, had sex with girls because they were curious or wanted to verify their sexual identity. Love and pleasure were motives for having sex with boys for BG. They were common reasons for potentially having sex with either sex among sexually inexperienced girls, but both were more likely for BG than LG for sex with boys. Internalized homonegativity did not mediate the relation between sexual identity and reasons for sex, but LG just with male partners were more homonegative than LG just with female partners. The findings indicate that LG and BG should not be combined into a single group, provide insights into the discordance between sexual identity and behaviors, and have implications for reducing risk for pregnancy and sexually transmitted infections among sexual minority girls.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".