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Rumblings in the West

2019· book-chapter· en· W2973590017 on OpenAlexaboutno aff
Vincent DiGirolamo

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicAmerican History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsFrontierNewspaperMilitantSocial capitalCapital (architecture)GeographyPolitical scienceCompetition (biology)American westIndividualismCapital cityEthnic groupEthnologyEconomic historyArchaeologyHistoryEconomic geographyPoliticsLawEcology

Abstract

fetched live from OpenAlex

Abstract No newsboys were more militant than those on the urban frontier. Though primarily self-employed, most identified with the interests of labor over capital, as reflected by the many unions and protests they organized between the 1880s and early 1900s. Newsboys mounted strikes and boycotts in Arizona, California, Colorado, Idaho, Missouri, Oregon, Utah, and Washington. They distributed union circulars and marched in Labor Day parades. Boys also distributed newspapers in the Hawaiian Islands and Yukon gold fields. Western newsboys represented all races and ethnicities, including Native Americans. They encountered work hazards unknown to their eastern counterparts, such as mountain lions, prairie fires, and gunfighters. Like the newspaper they sold, these children were catalysts of social change. As rugged individualists who relied on cooperation more than competition, they exemplified the contradictory values of their communities.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.038

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 studies0.0040.004
Scholarly communication0.0050.004
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.016
GPT teacher head0.186
Teacher spread0.169 · 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
Published2019
Admission routes1
Has abstractyes

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