ESG performance and corporate labor investment efficiency: Evidence from China
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
This paper investigates the impact of ESG (Environmental, Social, and Governance) performance on corporate labor investment efficiency in the Chinese market. We find that ESG performance can enhance labor investment efficiency. Additionally, this paper identifies that managerial myopia and the lack of financial expertise among management can hinder the positive effects of ESG on labor investment efficiency. Further, we discover that ESG can improve labor investment efficiency through the mediating role of R&D investments. Moreover, ESG tends to be more effective in enhancing labor investment efficiency in non-state-owned enterprises , in enterprises with low labor intensity , and in those that are in the growth or maturity stages of their business cycle. The conclusions remain robust after addressing issues of endogeneity, selection bias, and other methodological concerns. Overall, this paper enriches our understanding of the relationship between ESG and corporate labor investment efficiency.
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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 | 0.000 |
| 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