Multiple Victimization & Sexual Revictimization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Committing multiple victimization and sexual revictimization towards others can be labeled inhuman crimes that cause various forms of trauma to victims. In return, this results in higher mortality and tarnishes the connections between members of society. Five thousand three hundred people were used as a sample amount for the survey. The researcher wanted to know how people experiencing multiple victimizations and sexual revictimization can cause strain to one’s social life. The researcher also wanted to explore the connections to higher mortality rates as a result of the multiple victimizations and/or sexual revictimization to an individual. Results show that typical victims are those with little income and with an age range of 18 – 25; however, typical victims of sexual revictimization are usually outdoors during high-crime hours and with an age range of 18 – 25. With a lack of support, information and professionals with adequate experience to help those experiencing these offenses, victims resort to drugs, sex, and crime to ease their pain, making them feel alone in the world.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it