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Record W1544197200

Anchoring the Law in a Bed of Principle: A Critique of, and Proposal to Improve, Canadian and American Hearsay and Confrontation Law

2012· article· en· W1544197200 on OpenAlexaboutno aff
Mike Madden

Bibliographic record

VenueBoston College international and comparative law review · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsHearsayLawJurisprudenceConfrontation ClauseAdmissible evidenceArgument (complex analysis)Context (archaeology)Political scienceCommon lawSociologyHistory
DOInot available

Abstract

fetched live from OpenAlex

As recent case law demonstrates, both American Sixth Amendment Confrontation Clause jurisprudence and Canadian common law relating to hearsay evidence are conceptually problematic. The laws are, at times, internally incoherent and are difficult to justify on the basis of legal principles. This Article critiques confrontation and hearsay law in the United States and Canada, respectively, by exposing the lack of principle underlying each body of law. The Article develops a principled basis for evidence law in general, and hearsay and confrontation law in particular, providing a more stable foundation for hearsay and confrontation frame-works. Ultimately, the Article argues that the epistemic, truth-seeking goal of criminal evidence law is best served by the broad admission, rather than exclusion, of all hearsay evidence. Furthermore, while fairness concerns are relevant to some rules of evidence, there are no valid fairness concerns operating in the context of hearsay and confrontation law that should displace the primary principle of facilitating and promoting epistemically accurate fact-finding in criminal trials. Finally, this Article suggests that any dangers associated with the broad admission of hearsay evidence can be mitigated through effective argument by counsel and appropriate cautions to the trier of fact regarding any weaknesses inherent in the evidence.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.989
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.055
GPT teacher head0.395
Teacher spread0.339 · 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 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
Published2012
Admission routes1
Has abstractyes

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