Industrial disputes during the Rudd-Gillard era: Comparative perspectives and realities
Bibliographic record
Abstract
This paper examines industrial disputes during the Rudd-Gillard political era. Claims made in the public arena implying a steep rise in the volume of disputes are tested. The analyses of other academic researchers are updated in the light of a longer run of data being now available. Among other things, it is found that during the entirety of the Rudd-Gillard era the (per-quarter) volume of disputes was proportionately larger during the second half of the era than during the first half. Also, during the time that the Work Choices Act was operative, the (per-quarter) volume of disputes was around half of that experienced during the Rudd-Gillard era. A different perspective on these data is gleaned, however, when making longer-term comparisons. Two preceding political eras are compared: the Howard Era of 1996-2007 and the Hawke-Keating era of 1983-1996. In its entirety, the Rudd-Gillard era registered a far lower volume of disputes than that registered in the earlier eras. The long term (three-decade) decline in the volume and frequency of disputes is noted and a number of hypothesised explanatory factors are discussed.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".