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Record W3097369279 · doi:10.7202/1072347ar

From Industrial to Social Campaigns: Lay Morality, General Elections and Australia’s Trade Union Federation

2020· article· en· W3097369279 on OpenAlexvenueno aff
Donella Caspersz, Tom Barratt

Bibliographic record

VenueRelations industrielles · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsLegitimacyMoralityChampionPower (physics)Political scienceSociologyWork (physics)Public administrationIndustrial relationsTrade unionPolitical economyPublic relationsLawPoliticsEconomics

Abstract

fetched live from OpenAlex

This article considers the potential for union revitalization through campaigning in general elections. It first charts changes in unions’ campaigns in general elections, moving beyond a focus on industrial relations issues towards issues of social significance, such as health and education. Second, by reconceptualizing this activity using lay morality, unions may enhance their ability to increase their power and legitimacy. Thus, by acting in this way, unions can broaden the bases for their legitimacy and build new opportunities for their renewal. However, this approach may not lead to revitalizing their density, but may open the opportunity for their renewal because this approach consolidates their legitimacy to a broader constituency. We suggest that when unions act in this way, they become agents of social utility who champion the interests of a wider constituency. We argue that, given the dynamics of changes to work and the ways in which workers now work, this provides one route for unions to tap into these multiple subjectivities of workers and remain relevant. This article combines an analysis of over 1000 media articles that cover four periods of campaigns by peak unions in Australian elections between the years 2007-2016, with original interviews with key informants and an analysis of electoral survey results for each election to provide the discussion. These three methods triangulate to establish the shift in unions’ campaign focus and to suggest that this is a potential path to revitalization.

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)0.006
metaresearch head score (Gemma)0.015
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.114
GPT teacher head0.333
Teacher spread0.219 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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