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Record W1822363874

Admissibility frameworks and scientific evidence: controversies in relation to shaken baby syndrome / abusive head trauma

2015· article· en· W1822363874 on OpenAlexaboutno aff
Marika Linnéa Henneberg

Bibliographic record

VenueBritish Journal of American Legal Studies · 2015
Typearticle
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsShaken baby syndromeVerdictScientific evidenceCriminologyPsychologyLawChild abusePolitical sciencePoison controlSuicide preventionMedicineEpistemologyMedical emergencyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Criminal courts increasingly rely upon scientific evidence provided by expert witnesses. This raises a number of questions for the courts including what type of science they should admit and who should be allowed to give such evidence. The admissibility framework for scientific evidence in England and Wales (E&W) originates from the 1975 case of R v. Turner, [1975] QB 834. Under Turner, expert evidence is admissible as long as it is beyond the understanding of the fact-finders. This common law framework has been interpreted and developed and it now consists of a mismatch of court decisions from E&W, Australia, Canada and the United States of America (US). This framework does not seem to reflect the four decades of significant scientific advances that have taken place since Turner. There have been a number of prominent trials in the US and in E&W where scientific evidence has been associated with an improper verdict. This paper suggests that controversies related to Shaken Baby Syndrome (SBS) / Abusive Head Trauma (AHT) expose the weaknesses of admissibility frameworks in the US and, more specifically, in E&W. It concludes that the triad of symptoms frequently used to diagnose SBS/AHT is not reliable, and that courts need to consider more closely significant advances in the understanding of the symptoms previously believed to indicate that an infant had been shaken, before admitting such evidence in court.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.338
Teacher spread0.294 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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