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Record W1978543247 · doi:10.1353/tlj.2004.0002

Varieties of Vagueness

2004· article· en· W1978543247 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUniversity of Toronto Law Journal · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsVaguenessPhilosophyLinguisticsFuzzy logic

Abstract

fetched live from OpenAlex

It will surprise no one to hear that laws are often vague, and, moreover, that laws are vague for a variety of reasons. Some vagueness results from specific intentions of users of legal language. Laws may be poorly drafted, or drafted using general terms intended to capture a wide yet unspecified range of affairs. Vagueness of these kinds is, for the most part, noticeable yet bearable. Poor drafting can be fixed, and open-textured laws can sometimes be made more specific if their application proves troublesome. Yet in the trade-off between specificity and openness, a more peculiar kind of vagueness seems intrinsic to the nature of some legal norms. Their open texture cannot be sharpened to a univocal statement of what they require: they are indeterminate, leaving borderline cases where judges lack legal resources to resolve a dispute one way or another. At least part of the difficulty in handling norms of this sort comes from the mixture of reasons for their vagueness. When we observe, for example, that the Canadian Charter of Rights and Freedoms contains a vague provision permitting 'reasonable limits' 1 on fundamental rights and freedoms, we recognize also that mere understanding of the meaning of 'reasonable' goes only so far in dissolving its vagueness. 'Reasonable limits' are not just any artefacts of language use. They are normative standards, notoriously elastic and insusceptible to univocal and final statement in application to concrete cases. Here the real trouble begins: there is at least the air of paradox in the contrast between the fact of vagueness in laws and the opposed determinacy demand intrinsic to the rule of law -the requirement that laws be framed in a way that makes them capable of being obeyed. When has meaning been stretched too far? What justifies judicial setting of borders on the application of indeterminate propositions of law? After all, if 'reasonable limits' have no determinate edges, our most fundamental rights and freedoms have no inviolable borders, and the rule of law has failed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.194
Teacher spread0.178 · 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