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Record W4317717630 · doi:10.1111/chso.12691

Adultification, neglect and sexual abuse at home: Selected narratives of orphaned girls in KwaMashu, South Africa

2023· article· en· W4317717630 on OpenAlexfundno aff
Ndumiso Daluxolo Ngidi, Emmanuel Mayeza

Bibliographic record

VenueChildren & Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
FundersInternational Development Research CentreNational Institute for the Humanities and Social Sciences
KeywordsNeglectVulnerability (computing)Sexual abusePsychological interventionDomestic violencePsychologyChild abuseChild neglectDevelopmental psychologyPoison controlSuicide preventionPsychiatryMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract This paper explores two orphaned girls' accounts of victimization and vulnerability to child sexual abuse in their family homes. Interviews with these girls revealed a trend of neglect, adversity and processes of adultification which involved accounts of sexual abuse within their family homes. According to the data, the participants are vulnerable and they experience victimization as they are routinely sexually abused by older male relatives and non‐related men and boys inside their family homes – where they are supposed to feel safe and protected. We argue that these two young girls' experiences need to be understood as consequences of the prevailing cultures of toxic heteropatriarchal masculinities which have produced and normalized the distribution of male power over girls. The kinds of interventions required to address toxic masculinities and to insulate orphan girls from sexual abuse and neglect are also discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.010
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.013
GPT teacher head0.253
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2023
Admission routes1
Has abstractyes

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