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Record W2053878004 · doi:10.1093/jahist/96.2.568

How Cities Won the West: Four Centuries of Urban Change in Western North America. By Carl Abbott. (Albuquerque: University of New Mexico Press, 2008. x, 347 pp. $34.95, ISBN 978-0-8263-3312-4.)

2009· article· en· W2053878004 on OpenAlexaboutno aff
Charles N. Glaab

Bibliographic record

VenueJournal of American History · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipFrontierHistoryTheme (computing)ImmigrationEmpireGeographyEconomic historyArchaeologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This ably conceived and especially readable study narrates over four centuries of the urban history of western North America—the area from the Gulf of Mexico to the Mississippi River and the Mexican border. Carl Abbott, a distinguished urban historian, in fifteen sometimes very brief chapters incorporates extensive urban scholarship on early cities as seats of empire; urban rivalry as a central theme of early city history; garden, mining and tourist cities; water and the city based on irrigation; distinctive western city building and housing patterns (the emergence of the bungalow and the creative architecture of Los Angeles, for example); and immigration, ethnicity, and race. In his later chapters he argues that since the 1940s western cities have ceased to be reflective of general change and have been transformed into primary instruments in a process of global transformation. The author, to cite only one example of original scholarship, makes a significant contribution to the standard conception of western cities as spearheads of the frontier with his discussion of the founding of north-south gateway cities extending from Winnipeg to San Antonio. The scholarship discussed in the extensive chapter bibliographies and detailed notes make this brief book a valuable reference tool as well as an unusually readable general account.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.175
Teacher spread0.163 · 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 designNot applicable
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

Citations0
Published2009
Admission routes1
Has abstractyes

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