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Record W3213629759

Inalienable Properties : The Political Economy of Indigenous Land Reform

2020· book· en· W3213629759 on OpenAlexaboutno aff
Jamie Baxter

Bibliographic record

VenueeYLS (Yale Law School) · 2020
Typebook
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPoliticsLand reformPolitical scienceEconomic systemPolitical economyEconomicsEconomyGeographyDevelopment economicsAgricultureArchaeologyEcology
DOInot available

Abstract

fetched live from OpenAlex

As many Indigenous communities return to self-governance and self-determination, they are taking their own approaches to property rights and community development. Why did the Nisga’a Nation introduce property rights that can be traded in the market? And how have communities such as the Membertou First Nation sustained control over their lands in the face of economic pressures for saleable rights? This book explores the contrasting approaches to land rights illustrated by four Indigenous communities in Canada – the Westbank, Membertou, Nisga’a, and James Bay Cree Nations. Jamie Baxter traces how local leaders set the course of land rights and development in their communities during formative periods of legal and economic upheaval. Drawing on new research about institutional change in organizational settings such as business firms and labour unions, Baxter uses game theory to explore how community leaders have sustained inalienable land rights without turning to either persuasion or coercive force – the two levers of power normally associated with political leadership. Inalienable Properties challenges the view liberalized land markets are the inevitable result of legal and economic change. It shows how inalienability can result from intentional choices and is linked to structures of decision-making that have long-lasting consequences for communities.

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 score0.930
Threshold uncertainty score0.606

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.196
Teacher spread0.177 · 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
Published2020
Admission routes1
Has abstractyes

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