The Impact of Social Media, the Internet, and Legislation on Online Minor Sex Trafficking
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
This paper examines the impact of social media and the internet on the online sex trafficking of minors and assesses the impact of internet laws and legislation designed to stop online sex trafficking. Online sex trafficking of minors has been identified as a significant problem in North America and around the world, generating approximately 32 billion dollars annually. The expansion of the internet over the past 20 years has provided sex traffickers with a new way to conduct business. This article provides a review of the literature (studies, reports, gray material) published between 1996 and 2022. A review of statistics, the role of the trafficker and the characteristics of the victims provide context to the discussion of anti-trafficking laws and legislation. This review was conducted using a critical social theories lens to determine inherent bias in the work, presumed assumptions, structural inequalities, and how the growth of the internet has impacted social change. Findings indicate that the laws and legislation designed to protect victims of sex trafficking have been largely ineffective and that ethical considerations and biased results limit the methodology of many studies.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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