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Record W3121497906

Less Evidence, Better Knowledge

2015· article· en· W3121497906 on OpenAlex
Kenneth M. Ehrenberg

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsnot available
Fundersnot available
KeywordsHearsayContextualismEpistemologyArgument (complex analysis)Context (archaeology)JuryAdmissible evidenceAttributionLawLaw and economicsPolitical sciencePhilosophySociologyPsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

In his 1827 work Rationale of Judicial Evidence,
\nJeremy Bentham famously argued against
\nexclusionary rules such as hearsay, preferring a
\npolicy of “universal admissibility” unless the declarant
\nis easily available. Bentham’s claim that all
\nrelevant evidence should be considered with appropriate
\ninstructions to fact finders has been particularly
\ninfluential among judges, culminating in
\nthe “principled approach” to hearsay in Canada articulated
\nin R. v. Khelawon. Furthermore, many
\nscholars attack Bentham’s argument only for ignoring
\nthe realities of juror bias, admitting universal
\nadmissibility would be the best policy for an
\nideal jury. This article uses the theory of epistemic
\ncontextualism to justify the exclusion of otherwise
\nrelevant evidence, and even reliable hearsay, on
\nthe basis of preventing shifts in the epistemic context.
\nEpistemic contextualism holds that the justification
\nstandards of knowledge attributions
\nchange according to the contexts in which the attributions
\nare made. Hearsay and other kinds of
\ninformation the assessment of which rely upon fact
\nfinders’ more common epistemic capabilities push
\nthe epistemic context of the trial toward one of
\nmore relaxed epistemic standards. The exclusion of
\nhearsay helps to maintain a relatively high standards
\ncontext hitched to the standard of proof for
\nthe case and to prevent shifts that threaten to try
\ndefendants with inconsistent standards.

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.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.230
GPT teacher head0.417
Teacher spread0.187 · 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