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Record W4385961918 · doi:10.1163/9789004688797

Dangerous Anarchist Strikers

2023· book· de· W4385961918 on OpenAlexaboutno aff
Steve J. Shone

Bibliographic record

Venuenot available
Typebook
Languagede
FieldSocial Sciences
TopicAnarchism and Radical Politics
Canadian institutionsnot available
Fundersnot available
KeywordsMilitantCommunismPolitical scienceEconomic historyDirect actionGeneral strikeTrade unionLawHistoryPolitical economySociologyPoliticsEconomics

Abstract

fetched live from OpenAlex

This book explores the ideas of three largely forgotten radical women who participated in labor union strikes in Argentina and Uruguay, Canada, and the United States: Virginia Bolten (c.1876-1960), one of the most militant anarchists of southern South America; Helen Armstrong (1875-1947), a major leader of the Winnipeg General Strike of 1919, whose involvement in that important event in Canadian history was, for a long time, obscured by accounts that emphasized the accomplishments of men; and Elizabeth Gurley Flynn (1890-1964), the Wobbly leader who directed many industrial strikes throughout the United States, and was one of the founders of the American Civil Liberties Union, who eventually became the leader of the Communist Party, USA. It also examines the contributions of two similarly neglected anarchist men who participated in labor union strikes and industrial action in New Zealand, Australia, Chile, Argentina, and Japan. Tom Barker (1887-1970) was an anarchist who eventually became a socialist who worked to promote labor unionism on four continents and who tried to create a global One Big Union for sailors. Kōtoku, Shūsui (1871-1911) was a liberal who became a socialist and finally an anarchist. An opponent of governmental imperialism and ecological mismanagement, he studied and translated the works of Western thinkers and sought to apply what he learned from other cultures to the development of Japan.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.023

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 head0.040
GPT teacher head0.317
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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 routes1
Has abstractyes

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