Child sexual abuse: Raising awareness and empathy is essential to promote new public health responses
Bibliographic record
Abstract
Child sexual abuse is a major global public health concern, affecting one in eight children and causing massive costs including depression, unwanted pregnancy, and HIV. The gravity of this global issue is reflected by the United Nations' new effort to respond to sexual abuse in the 2015 Sustainable Development Goals. The fundamental policy aims are to improve prevention, identification, and optimal responses to sexual abuse. As shown in our literature review, policymakers face difficult challenges because child sexual abuse is hidden, psychologically complex, and socially sensitive. This article offers new ideas for international progress. Insights about needed strategies are informed by an innovative multidisciplinary analysis of research from public health, medicine, social science, psychology, and neurology. Using an ecological model comprising individual, institutional, and societal dimensions, we propose that two preconditions for progress are the enhancement of awareness of child sexual abuse, and of empathic responses towards its victims.Journal of Public Health Policy advance online publication, 12 May 2016; doi:10.1057/jphp.2016.21.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".