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Record W3123960466 · doi:10.22329/il.v36i3.4719

Anything Goes: An Apology for Parallel Distributed Legal Science

2016· article· en· W3123960466 on OpenAlexvenueno aff
Jaap Hage

Bibliographic record

VenueInformal Logic · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsCoherence (philosophical gambling strategy)Interpretation (philosophy)Legal realismLegal scienceStrengths and weaknessesValue (mathematics)Legal professionEpistemologyLawPolitical scienceSociologyComputer sciencePhilosophyMathematics

Abstract

fetched live from OpenAlex

Doctrinal legal science seems to lack a proper method and purpose. This interpretation clarifies its value. The backbone of the argu- ment consists of two theses. The first is that coherence—in a sense unusu- al in law—plays a crucial role in legal science. The second is that doctrinal legal science is a social enterprise and this should be consid- ered in attempts to understand it. Based on these, a picture of doctrinal legal science is given consisting of parallel distributed constructions of consistent, comprehensive and ex- pansive sets of legal beliefs. Given this, seeming weaknesses of doctri- nal legal science turn out to be actual strengths.

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)0.028
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.028
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.057
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0070.042
Scholarly communication0.0120.034
Open science0.0040.011
Research integrity0.0110.023
Insufficient payload (model declined to judge)0.0110.002

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 head0.070
GPT teacher head0.412
Teacher spread0.342 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations2
Published2016
Admission routes1
Has abstractyes

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