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Record W3088099997 · doi:10.9734/jesbs/2020/v33i930253

Legal and Political Considerations Associated with the Cancellation of the Court Challenges Program of Canada

2020· article· en· W3088099997 on OpenAlexaffabout
Jonas Kiedrowski, William T. Smale

Bibliographic record

VenueJournal of Education Society and Behavioural Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsTrent UniversityThe Lung Association Saskatchewan
Fundersnot available
KeywordsJurisdictionLawGovernment (linguistics)ConstitutionPoliticsSupreme courtConservative governmentPolitical sciencePublic administrationInterpretation (philosophy)SubsidyDemiseSociology

Abstract

fetched live from OpenAlex

Unique in the Western world, the Court Challenges Program was an undertaking funded entirely by the Federal Government of Canada, without regard to jurisdiction, to subsidize legal test cases of national importance regarding the clarification and interpretation of language and equality rights guaranteed under Canada’s Constitution. This paper reviews the literature on the cancellation of the Court Challenges Program of Canada. Except from 1992 to 1994, when Brian Mulroney’s Conservative government withdrew all financial support for the program, it existed in its various institutional forms from 1978 to 2006, until Stephen Harper’s Conservative government cancelled it on September 25, 2006. In June 2008, the program was somewhat resurrected under the name of the Language Rights Support Program. This program, despite its questionable aspects, helped change the landscape of Canadian law in regards to access to services for Aboriginals, differently-abled people, the rights of women and sexual minorities, and access to education, health and the courts for those speaking minority languages. This paper examines the stormy history of the Court Challenges Program, explores criticisms of its administration, and considers the political motivations that led to the program’s demise in 2006 and subsequent resurrection in 2019.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.948

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 studies0.0010.002
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 head0.055
GPT teacher head0.315
Teacher spread0.261 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes2
Has abstractyes

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