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Record W3120489835

Can Liberal States Accommodate Indigenous Peoples

2020· book· en· W3120489835 on OpenAlexaboutno aff
Duncan Ivison

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2020
Typebook
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPolitical sciencePolitical economyGeographySociologyEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

The original – and often continuing – sin of countries with a settler colonial past is their brutal treatment of indigenous peoples. This challenging legacy continues to confront modern liberal democracies ranging from the USA and Canada to Australia, New Zealand and beyond. Duncan Ivison’s book considers how these states can justly accommodate indigenous populations today. He shows how indigenous movements have gained prominence in the past decade, driving both domestic and international campaigns for change. He examines how the claims made by these movements challenge liberal conceptions of the state, rights, political community, identity and legitimacy. Interweaving a lucid introduction to the debates with his own original argument, he contends that we need to move beyond complaints about the ‘politics of identity’ and towards a more historically and theoretically nuanced liberalism better suited to our times. This book will be a key resource for students and scholars interested in political theory, historic injustice, Indigenous studies and the history of political thought.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.013
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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 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

Citations45
Published2020
Admission routes1
Has abstractyes

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