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Record W2953966777 · doi:10.60082/2563-8505.1357

Reconciliation and the Constitution: A Transcript of the Roundtable

2017· article· en· W2953966777 on OpenAlexafffundabout
Amar Bhatia, Beverley Jacobs, Jonathan Rudin, Douglas Sanderson, Mark Walters

Bibliographic record

VenueSupreme Court law review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of WindsorMcGill UniversityUniversity of Toronto
FundersUniversity of Toronto
KeywordsConstitutionIndigenousHuman rightsAmnestyPolitical scienceLawPoliticsSupreme courtState (computer science)Indigenous rightsRefugeeSociology

Abstract

fetched live from OpenAlex

As described in the opening piece in this Volume of the Supreme Court Law Review, unprecedented national media and political attention was given to the relationship between Indigenous people and the Canadian state in 2016. As part of our conference, we asked a group of people to come together and talk about the future of the Constitution as a means or an obstacle to reconciliation with Indigenous peoples and First Nations in Canada. Amnesty International’s most recent global report on the State of the World’s Human Rights praised Canada’s action regarding refugees, but then noted that “[c]oncerns persisted about the failure to uphold the rights of Indigenous Peoples in the face of economic development projects”. We asked our panelists about the connection between the rhetoric of reconciliation and the situation on the ground. Would the Court continue to play a significant role in the development of section 35 Aboriginal rights? Are these discussions likely to play out in courts, at constitutional amendment conferences, or in the political arena?

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)0.034
metaresearch head score (Gemma)0.067
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: none
Teacher disagreement score0.086
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0260.013
Scholarly communication0.0130.008
Open science0.0040.009
Research integrity0.0240.036
Insufficient payload (model declined to judge)0.0100.002

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 head0.071
GPT teacher head0.327
Teacher spread0.256 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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