Factors Affecting Construction Labor Productivity in China: A Case Study of Chongqing
Why this work is in the frame
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Bibliographic record
Abstract
Labor productivity is an important indicator of Chinese construction industry development, so it has a positive influence on study the factors affecting construction labor productivity for the sustainable development in construction industry. Since Chongqing became one of Chinese municipality in 1997, construction industry had a rapid development. But the construction labor productivity in Chongqing is still low. Thus, this paper selects construction labor productivity data in Chongqing as the research object, and indicates labor productivity is affected by eight specific factors from economy, technology, capital, labor and management aspects. Based on the data, this paper uses principal component analysis (PCA) method and multiple linear regression (MLR) to analyze the relationship between labor productivity and affecting factors. The result reveals labor productivity in Chongqing is affected by the average wage in construction industry, GDP and construction and installation engineering investment. Meanwhile, a low labor productivity in Chongqing dues to a lack of technological innovation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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