The Dynamics of Internet Sexual Solicitation: Examining the Criminal Careers of Online Groomers
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
The criminal career approach has been widely employed in the context of sexual delinquency, contributing significantly to our understanding of the criminal activities of sex offenders. To date, no studies have examined the criminal trajectories of online groomers within the framework of a criminal career analysis. To address this gap, the primary objective of this paper is to analyze this group’s criminal trajectories to expand our knowledge on participation, frequency, duration, seriousness, and versatility. To achieve this, an LPA was thus conducted using a sample of 1201 online groomers. The results support the existence of multiple distinct trajectories followed by individuals who engage in online sexual solicitation of minors, revealing the presence of four distinctive profiles: one-timer groomers, versatile and late groomers, specialist sex offender groomers, and polymorphous and prolific groomers. The profiles differ based on the number and types of offenses committed, the duration of their criminal involvement, and the diversity of their criminal activities.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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