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Record W7137437004

Poor Man's Fortune

2020· other· en· W7137437004 on OpenAlexfundno aff
Jarod Roll

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersShelby Cullom Davis Center for Historical Studies, Princeton UniversityUniversity of Illinois at Urbana-ChampaignPittsburg State UniversityUniversity of Colorado BoulderUniversity of SussexYork UniversityPrinceton UniversityNational Endowment for the Humanities
KeywordsConservatismOpposition (politics)White (mutation)PoliticsGrassrootsSpanish Civil WarGovernment (linguistics)World War II
DOInot available

Abstract

fetched live from OpenAlex

White working-class conservatives have played a decisive role in American history, particularly in their opposition to social justice movements, radical critiques of capitalism, and government help for the poor and sick. While this pattern is largely seen as a post-1960s development, Poor Man's Fortune tells a different story, excavating the long history of white working-class conservatism in the century from the Civil War to World War II. With a close study of metal miners in the Tri-State district of Kansas, Missouri, and Oklahoma, Jarod Roll reveals why successive generations of white, native-born men willingly and repeatedly opposed labor unions and government-led health and safety reforms, even during the New Deal. With painstaking research, Roll shows how the miners' choices reflected a deep-seated, durable belief that hard-working American white men could prosper under capitalism, and exposes the grim costs of this view for these men and their communities, for organized labor, and for political movements seeking a more just and secure society. Roll's story shows how American inequalities are in part the result of a white working-class conservative tradition driven by grassroots assertions of racial, gendered, and national privilege.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.065
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0650.017

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 head0.124
GPT teacher head0.423
Teacher spread0.299 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueDirectory of Open access Books (OAPEN Foundation)→French-language works237,207→