Filicide in Africa: a systematic review
Bibliographic record
Abstract
BACKGROUND: Filicide, the act of a parent or parental figure killing their child, has been reported in various African countries. However, there is a lack of comprehensive reviews on the prevalence and associated factors of filicide across the African continent, which is characterized by diverse cultural beliefs and practices. This review aims to examine the prevalence and risk factors of filicide in Africa. METHODS: This review included studies on filicide in Africa, identified through searches in various databases (PubMed, Scopus, Africa Journal Online, and Google Scholar) using relevant keywords. The Mendeley reference manager was used to organize all identified articles and remove duplicate entries. A two-round screening process was conducted by two independent reviewers, with the final set of articles selected through mutual agreement. The quality of the studies was then assessed. RESULTS: Out of the 107 retrieved articles, only 15 were included in the review. These studies revealed diverse prevalence rates: 3.7% of total homicides, 1.38% of deaths from family violence, and 13.02% for autopsied children. Various potential risk factors for filicide were identified, including unwanted pregnancies, marital conflicts, family disputes and violence, low socio-economic status, mental health issues in perpetrators, and mental, physical, or neurological vulnerabilities in victims. Cultural beliefs were also recognized as contributing factors to filicide. CONCLUSION: Filicide is a complex and multi-dimensional issue influenced by various individual, familial, and societal factors. The review highlighted a high prevalence of filicide in Africa, shaped by these diverse factors.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".