Two Steps Forward, One Step Back: Australian Union Revival
Bibliographic record
Abstract
Australian union membership declined at over one per cent per annum through the 1990s, and unions now represent around a quarter of the workforce. The Australian Council of Trade Unions [ACTU] has pursued several strategies aimed at tackling this malaise. The central purpose of this paper is to chronicle two of these strategies: union restructuring and the move to an 'organising' model of trade unionism. These strategies were championed by the ACTU as key planks in encouraging union recruitment and retention. The union restructuring strategy was successful in reducing the number of federally registered trade unions from 326 to 142. However, according to one observer [Fairbrother 2000], the result of these mergers is the creation of large-multi-sector and occupational unions, beset by uneasy internal political alliances and class compromises. The move to an `organising' model of unionism has been met with successes on the one hand, and resistance on the other. There are still unions locked into the servicing model rather than adopting a dual or balanced approach of servicing and recruitment. It seems like these strategies are like the curate's egg - partly good and partly bad and not wholly satisfactory, especially in arresting the carnage associated with declining union membership.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".