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Record W904336888

Reply to Edmond & Roach and Susan Haack's Replies to Law's Treatment of Science: From Idealization to Understanding

2013· article· en· W904336888 on OpenAlexvenueno aff
Nayha Acharya

Bibliographic record

VenueDalhousie law journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsnot available
Fundersnot available
KeywordsIdealizationSubject (documents)LawPsychologyScientific evidencePhilosophySociologyEpistemologyPsychoanalysisPolitical scienceComputer scienceLibrary science
DOInot available

Abstract

fetched live from OpenAlex

I am grateful to Professors Edmond and Roach1 and Professor Haack2 for their thoughtful replies to my paper, Law's Treatment of Science: From Idealization to Understanding. Much like my experience after reading Contextual Approach to the Admissibility of the State's Forensic Science and Medical Evidence,3 and Haack's contributions,4 I have come away from reviewing Edmond and Roach and Haack's replies with a heightened awareness that the admissibility of scientific evidence is significant and complicated. Both replies have raised important concerns that have demanded further attention from me, which I turn to here. My response to Edmond and Roach's Reply is in Part I below, followed by my response to Haack's Reply in Part II.I. Reply to Edmond and Roach1. The asymmetrical demonstrable reliability approachIn ACA, Edmond and Roach argued that Crown expert evidence should be subject to a more onerous admissibility standard than defence expert evidence. In their Reply, Edmond and Roach notably deemphasize the asymmetrical approach that they advocate in ACA. In their recap of the position they advanced in ACA, Edmond and Roach comment that the asymmetrical aspects of their approach were qualified.5 Later in the Reply, the authors note that a slightly higher admissibility standard will have a range of system benefits regardless of whether it is applied asymmetrically or symmetrically,6 again destressing their asymmetrical approach. In addition, they express confusion over why I endorse the Goudge Recommendations, but not the approach they argue for in A CA, remarking that [i]n practice, the differences between the Goudge recommendations and our own proposal are...relatively minor.7 But the Goudge Inquiry Report did not recommend an asymmetrical model. By suggesting that their approach is not significantly different from the Goudge Inquiry approach, Edmond and Roach further diminish the importance of the asymmetrical aspect of their proposal.I acknowledge that in ACA, Edmond and Roach take note that their asymmetrical approach may not find widespread support, and that if that is the case, then they could live with an across the board application of demonstrable reliability for admissibility. But their argument in ACA undoubtedly calls for an asymmetrical approach to admissibility of expert evidence. In ACA, Edmond and Roach introduce their argument as follows:We are supportive of more demanding standards for the admissibility of expert evidence. Indeed, we go beyond current legal practice and proposals for reform to argue for demonstrable reliability whenever the state adduces expert evidence to support a criminal conviction (or induce a plea)...,4? the same time, we would recommend that expert evidence adduced by the defense need only satisfy a basic reliability threshold, but would require that judges apply admissibility standards in a robust contextual fashion even should our asymmetrical proposal, which places higher standards on the state, not find favour.8Throughout ACA, Edmond and Roach insist that their demonstrable reliability standard should be applied to incriminating expert evidence, clearly demonstrating the asymmetry of their approach. Indeed, they criticize the Law Commission of England and Wales for rejecting an asymmetrical admissibility model.9 The asymmetrical approach was also advocated in Edmond's paper, Pathological Science? Demonstrable Reliability and Expert Forensic Pathology Evidence, which was prepared as a research paper for the Goudge Inquiry. There, Edmond explained:The basic contention is that courts should not admit expert evidence adduced by the prosecution unless there are good grounds for believing that the evidence is reliable. Expressed more precisely, judges should not admit expert evidence adduced by the prosecution unless that evidence is demonstrably reliable.10It is not until their final remarks in ACA that a symmetrical approach is again given a brief mention. …

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.350
Teacher spread0.286 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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