Investigative Analysis of Neonaticide
Bibliographic record
Abstract
Neonaticide (defined as the killing of an infant within the first 24 hours of birth) has occurred throughout history for a variety of reasons. Law enforcement files involving 40 female offenders resulting in 41 infant deaths were examined. Descriptive and frequency statistics revealed that the majority of offenders were young women who had never been married and had no criminal or psychological history. However, approximately a quarter of the sample did not fit these characteristics, which has implications for broadening the scope of investigations. The findings of this research identified four main challenges associated with neonaticide investigations: (a) variation in offender characteristics and situational factors, (b) intermittent denial of the pregnancy, (c) the physical resiliency of the offenders, and (d) lack of documented mental health and criminal history. Correspondence should be addressed to Kristen R. Beyer, P.O. Box 6566, Fredericksburg, VA 22403; email: kristen.beyer@krbconsultants.com and/or Joy Lynn E. Shelton, FBI Academy - NCAVC, Quantico, VA 22135; email: jlshelton@fbiacademy.edu
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".