Impact of occasional overtime on construction labor productivity: quantitative analysis
Bibliographic record
Abstract
Scheduled and occasional overtime practices have been used frequently in the construction industry. Past research indicated that continuous scheduled overtime could have a negative effect on labor productivity. The impact of occasional overtime on productivity is generally expected to be less than the impact of scheduled overtime. However, few studies have evaluated the effects of occasional overtime on productivity, which is the main objective of this paper. Productivity data for 234 weeks were collected for quantitative analysis. The t test was performed initially to determine the statistical significance of the impact of occasional overtime. The assessment of productivity data samples revealed possible deviations from the normal distribution. The Wilcoxon rank sum test was implemented as an alternative to the t test. The results of quantitative analysis indicate that moderate levels of occasional overtime did not have a significant impact on productivity. Based on the findings in this study, the potential advantages of occasional overtime practices are discussed.Key words: construction industry, labor productivity, occasional overtime, normality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".