Bibliographic record
Abstract
The collective bargaining framework in Australia's Fair Work Act 2009 provides only limited options for mandatory arbitration of collective bargaining disputes (also known as interest disputes). Experience in the first six years of the legislation's operation shows that these avenues for arbitration are rarely utilised, because the statutory tests to activate them are so difficult to meet. Eight federal and provincial Canadian labour law statutes contain provisions for first contract arbitration (FCA), enabling the relevant labour relations board to determine a first collective agreement. This article concludes that FCA in Canada works as a vehicle to promote collective bargaining; and therefore has considerable potential to address the failure of the Fair Work Act effectively to address employer 'surface bargaining' tactics and long-running agreement disputes. A variation of British Columbia's extended mediation model of FCA is recommended as the most suitable for adaptation, with Australia's Fair Work Commission given discretion to assess whether bargaining disputes should move from conciliation to interest arbitration. This reform would assist in the attainment of the FW Act's stated objective to encourage collective bargaining, and give more workers access to above-award wages and employment conditions through collective agreements.
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 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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".