Omfanget av seksuelle krenkelser og overgrep i en norsk ungdomsbefolkning
Bibliographic record
Abstract
The prevalence of sexual offences and abuse within a Norwegian youth population. The aim of this cross-sectional school-based study is to present and discuss the prevalence of sexual abuse within a Norwegian population of young people at the age of 18. Contrary to some earlier Norwegian studies the response rate is fairly high and sexually abuse is more clearly defined. The results are compared with an earlier Norwegian study. A clear gendered pattern can be seen in the data: about a quarter of the young correspondents have experienced sexual offenses, among them 77 percent are girls while 90 per cent of the offenders are males. The same pattern appears in other Nordic studies. Most of the reported sexual offenses towards girls take place when they are in their early teens and the offender is usually a boy some years older, in his teens or early twenties. A sexually offended girl reports more often the use of force or physical violence during the event than an offended boy does. The family is an arena with relatively fewer reported cases of sexually abuse or offences in this study than those of earlier research. We cannot say if this implies a decrease of sexual abuse within the family in Norway but international studies indicate such a tendency in some western countries. To be able to see how the picture of sexual abuse develops in society across time, for instance in a youth population, well prepared prevalence studies should be done within regular time-intervals
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".