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Record W613864256

Calling power to account : law, reparations, and the Chinese Canadian head tax case

2005· book· en· W613864256 on OpenAlexaboutno aff
David Dyzenhaus, Mayo Moran

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInjusticeRedressLawStatutory lawPolitical scienceAppealSociology
DOInot available

Abstract

fetched live from OpenAlex

Preface and Acknowledgments Contributors Context and History Mack v. Attorney General of Canada: Equality, History, and Reparation David Dyzenhaus and Mayo Moran Litigating Injustice Avvy Go Legal Discrimination against the Chinese in Canada: The Historical Framework Constance Backhouse Can We Do Wrong to Strangers? Audrey Macklin The Head Tax Case and the Rule of Law: The Historical Thread of Judicial Resistance to 'Legalized' Discrimination John McLaren Limits on Institutional Capacity to Address Injustice The Limits of Constitutionalism: Requiring Moral Behaviour from Government Mary Eberts Delivering the Goods and the Good: Repairing Moral Wrongs Catherine Lu Rights and Wrongs, Institutions and Time: Species of Historic Injustice and Their Modes of Redress Jeremy Webber Redress for Unjust State Action: An Equitable Approach to the Public/Private Distinction Lorne Sossin Legal Theory and Gross Statutory Injustice Gross Statutory Injustice and the Canadian Head Tax Case Julian Rivers The Juristic Force of Injustice David Dyzenhaus Private Right and Public Wrong The Timing of Injustice Lionel Smith Mack v. Attorney General of Canada and the Structure of the Action in Unjust Enrichment Dennis Klimchuk A Brief History of Mass Restitution Litigation in the United States Anthony J. Sebok Time, Place, and Values: Mack and the Influence of the Charter on Private Law Mayo Moran Appendix I: Appellants' Factum Appendix II: Mack v. Attorney General of Canada - Judgment of the Ontario Court of Appeal Index

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.526
Threshold uncertainty score0.998

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 studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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.

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

Citations9
Published2005
Admission routes1
Has abstractyes

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