Description et déterminants des conceptions des enseignants de 4 pays méditerranéens sur l'éducation à la sexualité
Bibliographic record
Abstract
Nowadays, sex education contributes to public health not only with regard to the prevention of HIV/AIDS, other sexually transmitted infections and sex abuse, but it is also concerned with addressing aspects such as interpersonal relationships and psychosocial implications. The school setting has emerged as a unique environment for access to information and scientific knowledge that contribute to better understanding of the various dimensions of sexuality. Teachers' and future teachers' conceptions about sex education are analysed in this paper. Data were obtained from a questionnaire designed by the European Biohead-Citizen research project. Responses were received from 2 537 teachers from four Mediterranean countries (Tunisia, Lebanon, Morocco and France) who completed the questionnaire. The methodology is based upon analyses of core components that support the discovery of teachers' conceptions. Following that exercise, standardised factorial scores were calculated. Results for in-service and pre-service teachers show high correlations between their conceptions and national culture, religious beliefs, and level of academic training. Detailed results are presented and discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.001 | 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".