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Record W2013475796 · doi:10.1258/rsmmsl.44.4.311

Neonaticidal Mothers: Are more boys killed?

2004· article· en· W2013475796 on OpenAlexaff
Jacques D. Marleau, Myriam Dubé, Suzanne Léveillée

Bibliographic record

VenueMedicine Science and the Law · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversité du Québec à Trois-RivièresInstitut national de psychiatrie légale Philippe-Pinel
Fundersnot available
KeywordsHomicideDemographyMedicineSignificant differencePediatricsPsychologyInjury preventionPoison controlMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

Neonaticide refers to the homicide of a newborn of less than 24 hours old. Recently, certain authors have reported that only boys were victims (Dubé, 1998; Haapasalo and Petäjä, 1999). The aim of this study was to determine whether the proportion of male/female victims identified in the literature varied significantly from the official proportions of males/females at birth in countries of the Western World. Two types of study were taken into account to identify the victims' sex, namely, those presenting case reports and those presenting case series. A total of 420 neonaticides were included in our analyses. The majority of newborn victims were male (58.3%). However, there was no significant difference compared with the percentage of male births (51.4%). Based on the data collected, results indicate overall that a child's sex is not a significant factor associated with neonaticide.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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 designObservational
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

Citations10
Published2004
Admission routes1
Has abstractyes

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