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Record W4415257530

Shaken baby syndrome: a medical, scientific, and legal controversy

2025· preprint· en· W4415257530 on OpenAlexaff
Cyrille Rossant, Leila Schneps, Guillaume Sébire

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2025
Typepreprint
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsMcGill University
Fundersnot available
KeywordsChild abusePoison controlSuicide preventionValue (mathematics)Human factors and ergonomicsMedical lawIdentification (biology)Injury prevention
DOInot available

Abstract

fetched live from OpenAlex

Among the various forms of violence against children, shaking is one of the most severe. It involves young infants shaken by adults, presumably overwhelmed by their crying. Identified half a century ago, this form of abuse can cause severe or fatal neurological injuries, prompting prevention campaigns in France and worldwide. While the reality and dangerous consequences of shaking are undisputed, the medical identification of shaken infants-based on various types of observations (notably radiological and anatomo-pathological)-has been debated in academic, medical, and legal circles since the 1990s. These discussions on the scientific reliability of such 'medical diagnoses of child abuse' are supported by a vast body of literature, even though some institutional actors minimize or reject them.This article presents a non-systematic review of these debates through a brief historical overview of the controversy and a concise discussion of the key medical, scientific, and legal issues. Significant developments have emerged in the understanding of shaken baby syndrome, including the nature and pathophysiology of associated injuries, the evidentiary value of available literature, and the forensic reliability of the diagnosis. The necessity of child protection explains why these academic debates are intertwined with legal, political, and societal issues. However, this same imperative calls for moving beyond polarization to achieve a more effective and reliable detection of child abuse.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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