The Irish study of sexual health and relationships sub-report 1 learning about sex and first sexual experiences
Bibliographic record
Abstract
Sex and sexuality (see glossary for definitions) has been a relatively taboo subject until \nrecent decades in Ireland, as elsewhere. Perspectives on sex and sexuality in Ireland were \ntraditionally shaped to a large extent by the teachings of the Catholic Church. Sexual intercourse \nwas seen as appropriate only in the context of marriage, with the primary purpose of procreation.2 \nThroughout the 1960s and 1970s, a number of factors, including the wider availability of \npopular media, brought about greater liberalism and increased discussion about sex in Ireland. As \nwell, greater mobility, mainly of Irish people travelling abroad from the early 1980s, introduced a \nwhole generation to new perspectives on sexual norms. Church attendance fell over this time and \nthere was an increasing public challenge to the Catholic Church’s stance on issues such as access \nto contraception. These factors contributed to the development of significant legislative changes \nin the area of sexual health in the late 20th century. They resulted in increased availability of \ncontraception, legalisation of divorce, decriminalisation of homosexuality and right to information \non abortion.3 At the same time, education generally and sex education in particular have \nincreasingly become the responsibility of the State. Irish society has seen a process of increasingly \nliberal social norms.3 Evidence of this shift includes the separation of sex from a purely procreative \nfunction and the view that sex is no longer exclusively associated with marriage. \nThe investigation of sexual health and behaviour requires consideration of the range of \nfactors that can influence them. As well as individual factors, external or structural factors (social, \neconomic and environmental) can determine aspects of health and behaviour. The Department of \nHealth and Children’s (2000) National Health Strategy states in its objectives that “the \nachievement of health and well-being is not the responsibility of the individual alone”.4 A further \nobjective aims to provide support to disadvantaged groups so that everyone has the same \nopportunity to attain good health. These objectives highlight the role that external influences can \nplay in determining health, and make clear that it is unlikely that individuals will be able to directly \ncontrol external determinants of health.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".