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Record W4367836609 · doi:10.1093/whq/whad069

The River That Made Seattle: A Human and Natural History of the Duwamish. By BJ Cummings

2023· article· en· W4367836609 on OpenAlexaffabout
J. Edward Taylor

Bibliographic record

VenueWestern Historical Quarterly · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNatural historyIndex (typography)Natural (archaeology)HistoryEnvironmental ethicsArchaeologyArt historyPhilosophyBiologyEcologyComputer science

Abstract

fetched live from OpenAlex

Seattle’s environmental history is having a moment. Since 2006, no less than seven books have historicized its animals, hinterlands, Indigenous landscapes, parks, protests, and waterways. Aside from Coll Thrush’s Native Seattle (Seattle, 2007), however, little explains how particular communities experienced environmental change. Activist BJ Cummings seeks to fill this lacuna by tracing the fate of nature and people along the lower Duwamish River, a tiny but massively changed stream. The River That Made Seattle is a fine-grained study of how the Doo-Ahbsh (now Duwamish Tribe) and their neighbors endured multiple environmental disruptions. Cummings seeks clarity, but this muddy river only produces muddy tales. The book’s first half explains how treaty councils obtained Native lands, ignited warfare, and enabled industrialization. Many Doo-Ahbsh resisted colonial displacement, but when their rebellion failed, they lost their claim to a separate reservation. Surviving families had to enroll in other tribal reservations or intermarry and homestead along the river. When industrialization straightened the Duwamish for shipping and manufacturing, toxic byproducts seeped into the ground, water, animals, and humans. Much of this story is documented more ably by Alexandra Harmon, Matthew Klingle, Corey Larson, Jennifer Ott, Lissa Wadewitz, David Williams, and Thrush, but Cummings’s use of Doo-Ahbsh family histories deepens our understanding of how Indigenous people persisted in place.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0390.007

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 head0.021
GPT teacher head0.201
Teacher spread0.180 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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