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Indigenous Peoples, the League of Nations, and International Law

2024· book-chapter· en· W4402640602 on OpenAlexaboutno aff
Sophie Rigney

Bibliographic record

VenueOxford University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousLeagueInternational lawPolitical scienceLawGeographyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract This chapter examines the relationships between the League of Nations, Indigenous peoples, and international law. The chapter analyses five appeals made by Indigenous people to the League between 1919 and 1938: from the Society of American Indians and Laura Cornelius Kellogg from Turtle Island America (1919); Anthony Martin Fernando from the territory now known as Australia (1921); Deskaheh from Turtle Island Canada (1923); TW Rātana and Pita Moko from Aotearoa New Zealand (1924); and Pearl Gibbs from Australia (1938). The chapter also examines the League’s response to these claims, and to questions of Indigenous peoples more generally, through analysing key concepts of sovereignty and statehood, and self-determination. The chapter argues that these Indigenous appeals represent a practice of Indigenous international law, with Indigenous peoples reiterating their sovereignty and nationhood, entering alliances with others, and appealing to a new internationalism to ground justice and law claims. In response, however, the League of Nations developed an imperial international law: one which denies Indigenous sovereignty and instead views states as sovereign, limits Indigenous self-determination while emphasizing the territorial integrity of states, and frames Indigenous rights through the prism of labour rather than rights to sovereignty and land. While the League offered the possibility of a new form of ‘justice’ for Indigenous peoples worldwide, ultimately the League’s development of imperial international law limited and denied Indigenous international law, and the implications of this continue to this day.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.980
Threshold uncertainty score0.984

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 studies0.0000.001
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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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