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Record W4391910495 · doi:10.1017/s0003055423001466

Late Homesteading: Native Land Dispossession through Strategic Occupation

2024· article· en· W4391910495 on OpenAlexafffund
Douglas W. Allen, Bryan Leonard

Bibliographic record

VenueAmerican Political Science Review · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaAustralian GovernmentNational Science Foundation
KeywordsSovereigntyIndigenousGovernment (linguistics)Threatened speciesPolitical scienceGeographyPolitical economyLawSociologyPoliticsEcology

Abstract

fetched live from OpenAlex

U.S. homesteading has been linked to establishing federal sovereignty over western lands threatened by the Confederacy, foreign powers, and the Indian Wars in the last half of the nineteenth century. However, the bulk of homesteading actually took place in the early twentieth century, long after these threats to federal ownership ceased. We argue that this “late homesteading” was also an effort to enforce federal rights, but in response to a different threat—a legal one. Questionable federal land policies in the late nineteenth century dispossessed massive amounts of Indigenous lands, and exposed the federal government to legal, rather than violent, conflict. Late homesteading was used to make the dispossession permanent, even in cases where a legal defeat eventually occurred. Examining the qualitative evidence, and using data on the universe of individual homesteads and federal land cessions across the 16 western states, we find evidence consistent with this hypothesis.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.334
Teacher spread0.298 · 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 designObservational
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

Citations19
Published2024
Admission routes2
Has abstractyes

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