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Record W2100130049

Indigenous Peoples at the Margin of the Global Economy: A Violation of International Human Rights and International Trade Law

2005· article· en· W2100130049 on OpenAlexaboutno aff
Arthur Manuel, Nicole Schabus

Bibliographic record

VenueChapman University Digital Commons (Chapman University) · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousHuman Development IndexMargin (machine learning)Index (typography)GeographyHuman rightsPopulationPolitical scienceSocioeconomicsDevelopment economicsEconomic growthEconomyHuman development (humanity)International tradeEconomicsDemographyLawSociologyEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

In the 1999 Human Development Report, which uses data from 1996 and 1997, Canada was ranked first among the 174 countries included in the report, and had the highest over all Human Development Index [HDI] score.Calculating HDI scores for Registered Indians, including those living on and off reserve, reveals a substantially lower HDI score for the Registered Indian population, which would be ranked about forty-eighth among the countries in the report. 1 I. INTRODUCTION: A WIDE RANGE OF INDIGENOUS RIGHTSOver the last three decades, Indigenous Peoples around the world have won important constitutional recognition of their inherent rights and jurisdiction.Yet, despite these gains, the socio-economic status of Indigenous Peoples has not improved and they continue to be the poorest populations of those countries * Arthur Manuel is a member of the Secwepemc Nation, in the South-Central Interior of British Columbia, Canada.He served as Chief of the Neskonlith Indian Band for eight years and as Chairperson for the Shuswap Nation Tribal Council for seven years.He also headed the Interior Alliance and currently serves as volunteer Chairperson for the Indigenous Network on Economies and Trade (INET).This paper is an ongoing case study and portions have been borrowed from an unpublished conference paper entitled Aboriginal Peoples v. Companies And Governments: Who are the Real Stewards of the Land and Forests?Growing International Understanding of Indigenous Proprietary Interests,

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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 designTheoretical or conceptual
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
Published2005
Admission routes1
Has abstractyes

Explore more

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