Are one-stop centres an appropriate model to deliver services to sexually abused children in urban Malawi?
Bibliographic record
Abstract
BACKGROUND: The Republic of Malawi is creating a country-wide system of 28 One-Stop Centres (known as 'Chikwanekwanes' - 'everything under one roof') to provide medical, legal and psychosocial services for survivors of child maltreatment and adult intimate partner violence. No formal evaluation of the utility of such services has ever been undertaken. This study focused on the experiences of the families served at the country's first Chikwanekwane in the large, urban city of Blantyre. METHODS: One hundred seven families were surveyed in their home three months after their initial evaluation for sexual abuse at the Blantyre One Stop Centre, and 25 families received a longer interview. The survey was designed to inquire what types of initial evaluation and follow-up services the children received from the medical, legal and social welfare services. RESULTS: All 107 received an initial medical exam and HIV testing, and 83% received a follow-up HIV test by 3 months; 80.2% were seen by a social welfare worker on the initial visit, and 29% had a home visit by 3 months; 84% were seen by a therapist at the initial visit, and 12% returned for further treatment; 95.3% had an initial police report and 27.1% ended in a criminal conviction for child sexual abuse. Most of the families were satisfied with the service they received, but a quarter of the families were not satisfied with the law enforcement response, and 2% were not happy with the medical assessment. CONCLUSIONS: Although a perception of corruption or negligence by police may discourage use of service, we believe that the One-Stop model is an appropriate means to deliver high quality care to survivors of abuse in Malawi.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".