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Record W7094787509

9781000342390.pdf

2020· other· en· W7094787509 on OpenAlexfundno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2020
Typeother
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversità degli Studi di PadovaUniversity of OxfordUniversity of CambridgeEuropean CommissionLondon School of Economics and Political ScienceResearch Centre for the HumanitiesPrinceton UniversityUniversity of ThessalyYork UniversityPurdue University
KeywordsPoliticsState (computer science)Law enforcementLeagueEspionageClass conflictSpanish Civil WarCapitalism
DOInot available

Abstract

fetched live from OpenAlex

This book provides a comparative and transnational examination of the complex and multifaceted experiences of anti-labour mobilisation, from the bitter social conflicts of the pre-war period, through the epochal tremors of war and revolution, and the violent spasms of the 1920s and 1930s. It retraces the formation of an extensive market for corporate policing, privately contracted security and yellow unionism, as well as processes of professionalisation in strikebreaking activities, labour espionage and surveillance. It reconstructs the diverse spectrum of right-wing patriotic leagues and vigilante corps which, in support or in competition with law enforcement agencies, sought to counter the dual dangers of industrial militancy and revolutionary situations. Although considerable research has been done on the rise of socialist parties and trade unions the repressive policies of their opponents have been generally left unexamined. This book fills this gap by reconstructing the methods and strategies used by state authorities and employers to counter outbreaks of labour militancy on a global scale. It adopts a long-term chronology that sheds light on the shocks and strains that marked industrial societies during their turbulent transition into mass politics from the bitter social conflicts of the pre-war period, through the epochal tremors of war and revolution, and the violent spasms of the 1920s and 1930s. Offering a new angle of vision to examine the violent transition to mass politics in industrial societies, this is of great interest to scholars of policing, unionism and striking in the modern era.

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 categoriesInsufficient 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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.966
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9540.847

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

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