Development of an internal benchmarking and metrics model for industrial construction enterprises for productivity improvement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Measuring and improving productivity in construction is a complex issue. This paper introduces the development of an internal benchmarking and metrics (BM&M) model for industrial construction enterprises to help them understand and implement mechanisms for continuously improving construction productivity. Processes are developed in the model for: (1) measuring and reporting craft labor productivity performance; (2) examining productivity influencing factors with respect to construction environment factors and construction practices implementation; (3) establishing a productivity performance evaluation model to understand mechanisms by which the environment factors and construction practices impact productivity; and (4) conducting strategic gap analysis of construction practices implementation. The model is validated on data collected by the designed BM&M process from an industrial construction company, which implemented the model. In conclusion, the model can be effectively used to understand the impact of practices implementation levels on productivity. This contributes knowledge towards implementation of productivity improvement methods in a company.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it