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Knights Across the Atlantic

2017· book· en· W4238664925 on OpenAlexaboutno aff
Steven Parfitt

Bibliographic record

VenueLiverpool University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIrishPoliticsHistoriographyWageIndustrial relationsMovement (music)HistoryPolitical scienceEconomic historyPolitical economyLawSociologyArt

Abstract

fetched live from OpenAlex

The Knights of Labor became the first national movement of American workers between 1869 and 1917. They also established branches of their movement across the world. This book explores the history of the Knights of Labor in Britain and Ireland, where between 1883 and the end of the century they organised upwards of 50 individual assemblies (branches) and 10,000 members across England, Wales, Scotland and Ireland. It treats the Knights as an important but under-recognised part of the great changes taking place within the British labour movement at the end of the nineteenth century, whether in terms of the growth of labour politics (and ultimately the Labour Party) or the transformation of the trade unions from the movement of a minority of wage earners to a majority of them. This book looks at the approaches that British and Irish Knights took to politics, industrial relations, race, culture and gender, drawing on and making comparisons with the well-established historiography of the Knights in Canada and the United States, and shows how British and Irish Knights tried and ultimately failed to make their American movement a permanent part of the British and Irish industrial landscape.

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)0.001
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 score0.361
Threshold uncertainty score0.726

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.003
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0600.011

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 head0.021
GPT teacher head0.221
Teacher spread0.200 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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