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Record W7027176367

Comprehensive Right to Repair: The Fight Against Planned Obsolescence in Canada

2023· article· en· W7027176367 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsObsolescenceCognitive reframingOverconsumptionPoliticsNew RightSeverance
DOInot available

Abstract

fetched live from OpenAlex

The comprehensive right to repair—one that addresses overconsumption and enables a circular economy—is an integral part of climate change policy in Canada. Where it is traditionally approached from an economic perspective, this article presents the right to repair as an instrument of environmental law. This reframing looks to France’s Anti-Waste and Circular Economy Law for structural and substantive elements of such legislation. Further, this article examines previous attempts to legislate the right to repair in Canada and explores how an overarching environmental purpose aids in overcoming political and jurisdictional barriers to its implementation. Ultimately, this article advocates for realization of a comprehensive right to repair through the updating of multiple pieces of existing federal 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.

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)0.007
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.143
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0280.019
Scholarly communication0.0110.004
Open science0.0030.006
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.261
Teacher spread0.244 · 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
GenreOther

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

Citations3
Published2023
Admission routes1
Has abstractyes

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