Limites des données autorapportées sur les comportements sexuels des adolescents
Bibliographic record
Abstract
La recherche sur des sujets sensibles comme la sexualité est sujette à divers biais liés aux caractéristiques des participants (ex. âge, genre, croyances au sujet de la sexualité, etc.), aux instruments de mesure utilisés (ex. journal de bord, questionnaire, entrevue, examen biologique), ainsi qu’à la formulation, l’interprétation et la spécificité des comportements évalués. Bien que typique et plutôt inévitable pour évaluer les comportements sexuels, le recours aux instruments autorapportés comporte son lot de défis méthodologiques et de critiques, en plus de soulever des questions additionnelles de validité et d’éthique lorsqu’ils s’adressent à des personnes mineures. La plupart des chercheurs conviennent qu’il serait souhaitable de prendre en considération les biais issus des fausses déclarations, mais très peu d’alternatives sont disponibles. De plus, la majorité des études sur la sexualité des adolescents utilise des devis de recherches transversaux et rétrospectifs. De telles recherches sont sujettes aux difficultés de rappel et aux reconstructions mnésiques des événements a posteriori, surtout lorsque l’intervalle de temps écoulé entre l’événement et son rappel est important. Les rares études longitudinales observent qu’une proportion importante de participants rapporte des données incohérentes quant à l’occurrence et à l’âge de la première relation sexuelle, ce qui soulève des questionnements sur la justesse et la validité de certaines connaissances que nous croyons détenir sur les comportements sexuels des adolescents. Research on sensitive topics like sexuality is subject to diverse biases related to the characteristics of the participants (i.e. age, gender, beliefs about sexuality, etc.), the measurement selected (i.e. diary, questionnaire, interview, biological tests), and the wording, interpretation and specificity of the behaviors assessed. Although typical and quite inevitable in the field of sexual behaviors, the use of self-report assessments has its load of methodological challenges and critiques, and raises additional validity and ethical questions when used with minor participants. Most scholars agree that researchers should account for biases stemming from misreporting on sensitive information such as sex among young people, but very few alternatives for doing so are available. In fact, most studies have used retrospective cross-sectional designs, which have led to additional accuracy concerns, increasingly problematic as the length of the time period between the sexual event and the assessment expands. The rare longitudinal studies on sexual behaviors have found an impressive proportion of participants reporting inconsistent data both for the occurrence of sexual behaviors as well as for their age at first time, thus raising issues about the accuracy and validity of some of the knowledge on adolescent sexual behavior we claim from the current literature.
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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 | 0.170 | 0.497 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".