Does Geographical Proximity Affect Corporate Social Responsibility? Evidence from U.S. Market
Bibliographic record
Abstract
Corporate Social Responsibility is considered as a key corporate agenda in recent years. This study examines the relation between geographical proximity to metropolitan areas and corporate social responsibility. Methodologically, sample firms are classified by their distance to top-metropolitan area of Census 2010. Corporate social responsibility follows scoring system, which has been developed by the notable KLD Research & Analytics. Based on the samples from U.S. listed firms, the results support the main hypothesis that firm locating further from metropolitan areas tends to commit greater degree of social responsibility than those locating nearby top-metropolitan areas. Social responsible activities are exploited as a mean to alleviate information asymmetry and agency conflict rose from a distance. Besides, further investigation shows that the results above are potentially explained by some attributes of corporate social responsibility. These results are important to academic field because they show that the extent of any non-financial corporate activity, i.e. corporate social responsibility, can be explained by its geographical background.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".