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Record W2092488963 · doi:10.1017/s0008423906299967

Calling Power to Account: Law, Reparations, and the Chinese Head Tax Case

2006· article· en· W2092488963 on OpenAlexaffabout
Peter Li

Bibliographic record

VenueCanadian Journal of Political Science · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLawAppealSupreme courtPower (physics)Political scienceHead (geology)Common lawSociology

Abstract

fetched live from OpenAlex

Calling Power to Account: Law, Reparations, and the Chinese Head Tax Case, David Dyzenhaus and May Moran, eds., Toronto: University of Toronto Press, 2005, pp. 471. This is a collection of fifteen essays that addresses different aspects of the Chinese head tax case. Edited by two law professors and written mostly by lawyers and law professors, the collection has a strong legal flavour. The book begins with the legal case of Mack vs. Attorney General of Canada. However, the book does not provide a succinct summary of the case. In brief, the case involves three Chinese Canadians, Shack Jang Mack, Quen Ying Lee and Yew Lee, filing a statement of claim through their attorney in December, 2000, in a class action on behalf of head tax payers in the Ontario Superior Court. In all, the case went through three courts, and the original ruling dismissing the claim of head tax payers was upheld by the Court of Appeal and the Supreme Court.

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.503
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0130.022
Scholarly communication0.0070.003
Open science0.0020.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.336
Teacher spread0.318 · 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
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

Citations3
Published2006
Admission routes2
Has abstractyes

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