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Record W3208195773 · doi:10.1017/s0008423921000810

Occupancy, Land Rights and the Algonquin Anishinaabeg

2021· article· en· W3208195773 on OpenAlexaffabout
Veldon Coburn, Margaret Moore

Bibliographic record

VenueCanadian Journal of Political Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsQueen's UniversityUniversity of Ottawa
Fundersnot available
KeywordsJurisdictionTreatyState (computer science)Political scienceNegotiationGeographyArgument (complex analysis)LawOccupancyIndigenous rightsIndigenousHuman rights

Abstract

fetched live from OpenAlex

Abstract This article is about Indigenous territorial title and land rights, and specifically those of the Algonquin Anishinaabeg Nation. In 1983, the Algonquins of Pikwàkanagàn, residing in the province of Ontario, petitioned the Crown to recognize Algonquin territorial title and rights to 36,000 square kilometres of their natal homelands in the Ottawa River watershed. With negotiations beginning in the early 1990s, an Agreement-in-Principle was developed and ratified in 2016, the penultimate step to the largest modern treaty in Ontario's history. In this article, we examine the argument for moral rights to territory, not in terms of the Canadian or international legal order, nor even through examining the documents and voice of the Algonquin Anishinaabeg, but through the lens of an argument that has been advanced as the basis of the international territorial rights of states. We argue that the justifications for state rights territory—grounded in the considerations that ensue from an analysis of occupancy groups—provides a stronger claim to territorial jurisdiction and title in the case of the Algonquin Anishinaabeg Nation than the competing claim by the Canadian state.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.336
Threshold uncertainty score0.677

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.012
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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 designQualitative
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

Citations9
Published2021
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Political ScienceSame topicIndigenous Health, Education, and RightsFrench-language works237,207