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Record W2045389901 · doi:10.7202/1026154ar

Residual Radicalism

2014· article· en· W2045389901 on OpenAlexaffvenue
Richard MacKinnon, Lachlan MacKinnon

Bibliographic record

VenueEthnologies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsConcordia UniversityCape Breton University
Fundersnot available
KeywordsDeindustrializationMillCapeHistoryWorking classSociologyPolitical scienceArchaeologyPoliticsLaw

Abstract

fetched live from OpenAlex

The making of songs is an important, yet under-explored tradition amongst steel workers throughout North America. Steel making has been an essential part of Cape Breton Island’s economy and landscape since the mid-nineteenth century. The first steel mill was constructed in Sydney Mines in the 1870s; a larger mill was built in the newly emerging city of Sydney, the island’s largest centre, by 1901. Distinctive traditions of work and leisure began to emerge amidst the grid-patterned streets and company-owned homes of workers and managers. In the early years of the twentieth century, a close-knit working-class consciousness had taken root in the steel making centre of Sydney, Cape Breton Island. Songs explore topics such as the harsh conditions of work in the steel plant, personalities and places, tragedies, the industrial conflicts of the 1920s, and the attitudes of workers toward management. Many are often tinged with satire and witty analysis of working-class life. Sydney, as with many communities in North America, has profoundly experienced the process of deindustrialization in the latter part of the twentieth century. The last operating coal mines closed in Cape Breton the 1990s and the Sydney Steel plant shut its doors in 2000. This paper explores the questions: what role did songs about steel play in the development of class consciousness during the development of the steel industry in Sydney? Do songs play an equally significant role in the latter part of the twentieth century when the community was undergoing the process of deindustrialization? What types of songs about steel making and the steel mill are found in each of these significant periods in Sydney’s history? An exploration of some of these songs reveal much about how human beings respond to the processes of industrialization and deindustrialization.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.014
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0270.004

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 head0.052
GPT teacher head0.334
Teacher spread0.282 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations4
Published2014
Admission routes2
Has abstractyes

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