Research Trends On Technology-Assisted Child Sexual Abuse: A 20 Years Bibliometric Analysis
Bibliographic record
Abstract
Technology-Assisted Child Sexual Abuse (TA-CSA) is a critical issue. This study examines the trends of TA-CSA studies globally to understand the issues. Bibliometric analysis with VOSviewer was conducted on 840 selected journal articles published in the last 20 years from the Scopus database. Between 2002 and 2023, scientific articles on the subject were published by 89 countries, with the US, UK, and Canada being the top 3 countries with the highest publication in TA-CSA. Authors from the US and UK dominate research related to TA-CSA. Research on CSA is more related to medicine, psychology, and social science. TA-CSA research tends to increase, with the highest increase occurring in 2020. Bibliometric analysis also reveals researchers' concerns and research trends regarding TA-CSA. The consistent presence of clusters focusing on TA-CSA highlights the ongoing and persistent nature of this issue. Research in this area continues to explore various aspects, including the prevalence, risk factors, and the impact on victims. It emphasises policy evaluation and victims' access to and accept various forms of protection and assistance.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.130 | 0.206 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".