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Record W7005486301

R' Blake Brown, A Trying Question: The Jury in\nNineteenth-Century Canada

2009· article· en· W7005486301 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
Fundersnot available
KeywordsJuryDramaNarrativeContext (archaeology)DutySubject (documents)Legal cultureStatutory lawLegal historyDiscretion
DOInot available

Abstract

fetched live from OpenAlex

In a 1984 review essay on the inter-relationship(s) oflaw and society in English criminal law historiography, Doug Hay observed that "in history, there is no 'background," His point was that there are an infinite number ofbackgrounds, all of which are moving and changing, often in non-linear fashion, at different paces, either in counter-point or direct dialogue with the foreground which is the immediate subject ofexposition. Legal historians who put their topics "in context" by treating the background as static are now fortunately few, at least when this background is conceived of as social or economic. But as Hay observed, the most immediately significant context for any area of legal history is often itself legal, and it is this legal context-the institutions, the rules of procedure and evidence--of which legal historians need to be the most aware, but often take for granted. Not that this is entirely our fault: while we have ample secondary sources on many non-law aspects of nineteenth century Canadian society, the nittygritty of the system has not attracted the same interest. While there are compelling stories about eccentric judges, or the consequential narratives these individuals produced, to be celebrated, excoriated or otherwise deconstructed, it is a brave researcher who chooses to devote him or herself to the dry bones of statutory changes to faceless structures such as the jury. Popular culture may imbue juries with drama galore, but this is necessarily fictional, since where reasoning and communication are the duty of (modem era) high court judges, that ofjurors has been discretion and opacity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.813

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0260.019
Scholarly communication0.0110.006
Open science0.0030.003
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0120.001

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2009
Admission routes1
Has abstractyes

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