Productivity and industrial relations in the Australian construction industry
Bibliographic record
Abstract
The global construction industry has a poor productivity record compared with other industries. While there have been many studies into the factors that influence construction productivity, the role of industrial relations (IR) in construction productivity has been neglected. This is despite countries with highly unionised workforces, such as Australia and Canada, often attributing the industry’s relatively low productivity to its confrontational IR environment. This paper explores how construction project managers and operatives in Australia interpret what has become a highly divisive IR debate and how this influences their IR behaviour. A survey of 92 construction project managers and operatives reveals multi-theoretical perceptions influenced by both pluralist and radical IR theories. While unions are seen as beneficial to project safety and work hours, they are perceived as detrimental to productivity, although there is uncertainty about how this relationship works. It is concluded that improvements in construction project productivity are unlikely to be achieved by IR legislation alone but through a more complex multidimensional bargaining lens where project managers and operatives develop mutually beneficial shared solutions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".