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Record W160071724

Plain English in Quebec Legislation

2007· article· en· W160071724 on OpenAlex
Lena Day

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

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Language and Interpretation
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationStatuteMeaning (existential)Plain languageArgument (complex analysis)LawAffect (linguistics)Political sciencePlain EnglishLaw and economicsSociologyPsychologyMedicineCommunication
DOInot available

Abstract

fetched live from OpenAlex

Why is it that the average person, even a well-educated one, setting out to read a bill or law for the first time, half if not fully expects to have trouble cutting through the language to get to the meaning? It could be argued that bills and statutes use complex language because they address complex subjects¿taxation or securities regulation, for example¿or because they are meant mainly for people ¿in the know¿ such as members of lobby groups, practitioners in the fields concerned, lawyers and officials. The bottom line, though, is that laws affect everyone and this alone is a compelling argument for using idiomatic and understandable language. This article looks at efforts made by the Québec National Assembly to introduce plain English in its legislation.

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 score0.901
Threshold uncertainty score0.693

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 communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.297
Teacher spread0.289 · 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

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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