Bibliographic record
Abstract
Abstract Sexual aggression is defined as the offenders' act to impose his or her sexual will over another, nonconsenting, person using behaviors such as threats, intimidation, drugs, or physical force. Sexual aggression may happen to any person regardless of his/her socioeconomic status, education, race/ethnicity, sexual orientation, and so forth. Historically, women have been treated by men as “property” and, thus, sexual aggression against a woman was an act against the man (e.g., father, husband) who “owned” her. Sexual aggression may take place in a family environment or in a romantic relationship and it may be “condoned” by some fundamentalist religious laws. Sexual aggression often has a negative impact on victims' mental and physical health. Even though 9.1 percent of women in the United States have been forced to have their first sexual intercourse, this number is relatively low compared to other places (e.g., 40 percent in Peru). Over the years different theories (e.g., feminist, social learning) have proposed explanations as to why sexual aggression is common. Further, a number of techniques have been developed to attempt to treat sex offenders.
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 | 0.004 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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".