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Record W4406525671 · doi:10.5250/9781496245441

This Benevolent Experiment: Indigenous Boarding Schools, Genocide, and Redress in Canada and the United States

2015· book· en· W4406525671 on OpenAlexaboutno aff
Andrew Woolford

Bibliographic record

VenueUniversity of Nebraska Press eBooks · 2015
Typebook
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsRedressIndigenousGenocidePolitical scienceCriminologyGeographySociologyLawEcology

Abstract

fetched live from OpenAlex

At the end of the nineteenth century, Indigenous boarding schools were touted as the means for solving the “Indian problem” in both the United States and Canada. With the goal of permanently transforming Indigenous young people into Europeanized colonial subjects, the schools were ultimately a means for eliminating Indigenous communities as obstacles to land acquisition, resource extraction, and nation-building. Andrew Woolford analyzes the formulation of the “Indian problem” as a policy concern in the United States and Canada and examines how the “solution” of Indigenous boarding schools was implemented in Manitoba and New Mexico through complex chains that included multiple government offices with a variety of staffs, Indigenous peoples, and even nonhuman actors such as poverty, disease, and space. The genocidal project inherent in these boarding schools, however, did not unfold in either nation without diversion, resistance, and unintended consequences. Inspired by the signing of the 2007 Indian Residential School Settlement Agreement in Canada, which provided a truth and reconciliation commission and compensation for survivors of residential schools, This Benevolent Experiment offers a multilayered, comparative analysis of Indigenous boarding schools in the United States and Canada. Because of differing historical, political, and structural influences, the two countries have arrived at two very different responses to the harm caused by assimilative education.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.739
Threshold uncertainty score0.832

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 studies0.0010.002
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 head0.017
GPT teacher head0.214
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations108
Published2015
Admission routes1
Has abstractyes

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