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Record W2301656794 · doi:10.29173/alr358

Determinate/Indeterminate Duality: The Necessity of a Temporal Dimension in Legal Classification

2015· article· en· W2301656794 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueAlberta Law Review · 2015
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsMcGill University
Fundersnot available
KeywordsContext (archaeology)Indeterminacy (philosophy)Perspective (graphical)Computer scienceCLARITYProcess (computing)Artificial intelligenceEpistemology

Abstract

fetched live from OpenAlex

The objective of this article is to reconcile the difficulties in legal classification that arise when subject matter is viewed from a purely spatial, i.e., a two or three-dimensional, perspective. At issue is whether the dynamic complexity of legal reasoning can be represented through a process of static classification. The difficulty with traditional approaches to classification is that while legal reasoning makes use of concurrent concepts to resolve issues, classification systems operate with mutually exclusive classes that do not permit representation of reiterative reasoning processes. Using the example of the neologism of "propertization, "an issue of increasing concern in the field of intellectual property, demonstrate that a single classification system can represent both the delerminacy the author seeks to and indeterminacy of legal concepts as they are used to resolve legal problems without sacrificing the clarity presumably required for the rule of law to operate. Resolution requires adopting a classification system that makes use of both a temporal and spatial perspective. By adopting a temporal perspective in addition to a more traditional spatial perspective, we are able to expandour focus from the products of legal classification to legal classification as a process. We can then examine the dynamic relationship of relativity between legal concepts as they operate in context, rather than limiting our analysis to the static relationship of demarcation that exists when legal classes are examined in the abstract.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.841

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.067
GPT teacher head0.299
Teacher spread0.232 · 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