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Record W2796168702 · doi:10.29173/alr1332

In a Poor State: The Long Road to Human Rights Protection on the Basis of Social Condition

2003· article· en· W2796168702 on OpenAlexvenueaboutno aff
Lynn A. Iding

Bibliographic record

VenueAlberta Law Review · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCharterHuman rightsPovertyDenialPrejudice (legal term)Social rightsState (computer science)LegislationFundamental rightsInternational human rights lawGovernment (linguistics)Political scienceLaw and economicsSocial protectionLawSocial securityEconomicsBusinessPsychology

Abstract

fetched live from OpenAlex

This article examines how poverty in Canada might be alleviated with different forms of human rights protection that include protection from discrimination on the basis of social condition. Social condition discrimination could include denial of goods and services based on stereotypes of poverty, or could include disadvantage resulting from actual inability to pay. If based only on stereotypes, the author argues, social condition would be differentiated from other grounds of discrimination. Poor people need to be protected from the prejudice of others as well as the effects of being poor, and this may be accomplished by incorporating full social condition protection in both human rights legislation and the Canadian Charter of Rights and Freedoms. Canada has international obligations concerning poverty, and those obligations are sometimes recognized by the courts in their decisions. However, economic rights have been consistently rejected as having Charter protection, perhaps out of fear that courts would be commanding the government to create or alter social programs. The author concludes that the Charter might still be the most effective place for economic rights, placing the initial onus more on the public sphere, which would at the same time consequently distribute some of the financial burden in the private sphere.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.039
GPT teacher head0.342
Teacher spread0.303 · 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
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

Citations4
Published2003
Admission routes2
Has abstractyes

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