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Changing the Narrative: Settler Colonialism, Food and the Columbia River Treaty

2023· article· en· W4387122682 on OpenAlexaffvenueabout
John Wagner

Bibliographic record

VenueAnthropologica · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsTreatyColonialismIndigenousPolitical scienceDeclarationLawGeographyEcology

Abstract

fetched live from OpenAlex

While the written terms of the Columbia River Treaty appear to justify the often-heard claim that it is all about hydropower and flood control, a full account of its history reveals its critical importance to US agriculture and close relationship to early phases of colonization and development in the Upper Columbia River Basin. In this paper I argue that the Treaty is best understood as the third phase in the last large-scale government-sponsored settler colonialism project in North America, a project that began with the construction of the Grand Coulee Dam in the 1930s. I further argue that the dominant narrative that informs current efforts by Canada and the US to revise the treaty does not fully recognize the settler colonial structure of the original treaty or its critical impact on both Indigenous and settler food systems throughout the basin. I begin with a description of the history of the treaty, in order to demonstrate its continuity with earlier phases of settler colonialism, then focus on its impact on food systems. I conclude with an assessment of the ongoing Canada/US treaty review and renegotiation process that began in 2011 with suggestions for how the process could be brought into better alignment with the United Nations Declaration on the Rights of Indigenous Peoples and the Calls to Action of the Truth and Reconciliation Commission of Canada.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0350.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.386
Teacher spread0.338 · 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.

Study designQualitative
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

Citations1
Published2023
Admission routes3
Has abstractyes

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