Make-or-break during production: shedding light on change-orders, rework and contractors margin in construction
Bibliographic record
Abstract
A considerable amount of research has examined the cost performance of construction projects, yet there has been a paucity of studies that have examined the impact that client initiated change-orders and rework have on contractors. This paper seeks to add further clarity to this issue by replicating previous empirically-based research to establish the validity and reliability of the key issues influencing a contractor's cost performance. A total of 98 projects were used to examine the value of rework and change-orders and their influence on a contractor's margin. Only 65% of projects experienced a cost increase, though a mean rework cost of 0.39% of the contracted value was incurred. The difference between approved client change-orders and those by the contractor for subcontractors was 0.5% of the total costs incurred, which adversely impacted the organisation's profit. Margin losses may well have been higher as rework is seldom formally documented and reported.
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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 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".