Light and Heavy Heterosexual Activities of Young Canadian Adolescents: Normative Patterns and Differential Predictors
Bibliographic record
Abstract
The objectives of this research were to explore patterns of heterosexual activity in early adolescence and to examine the differential pathways to light and heavy heterosexuality. We utilized the National Longitudinal Survey of Canadian Children and Youth (NLSCY) in which heterosexual behaviors, as well as puberty, parenting processes, peer self‐concept, and problem behaviors were examined. The heterosexual activities of the majority of 12‐ and 13‐year‐old adolescents were largely confined to light activities of hugging, holding hands, and kissing. Heavy activities such as petting and sexual intercourse were reported less often. Using predictor variables from Cycle 1 of the NLSCY when participants were 10‐ and 11‐year‐olds, SEM analyses indicated that puberty and higher peer self‐concept shared significant direct pathways to both light and heavy heterosexuality. Heavy sexual activity, however, was uniquely associated with the risk factors of adolescent problem behaviors. Positive and hostile parenting styles were indirectly associated with light sexual activity through peer self‐concept. Positive and hostile parenting styles were also indirectly associated with heavy sexual activity through both peer‐oriented self‐concept and problem behaviors. Results support differential patterns and predictors of light and heavy sexuality in early adolescence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".