Corporate Social Responsibility and Financial Performance: A Cross-Cultural Analysis
Bibliographic record
Abstract
Based on the geographic limitations of previous meta-analysis made about Corporate Social Responsibility \n(CSR) and Financial Performance (FP) and on the evidence found in previous work on the country's \ninfluence in this relationship, the aim of this paper is to analyze the relationship between these two variables \nstudying the possible moderating effect that the country variable may have on it. \nBy the use of the cultural dimensions of GLOBE (2004), we classify the countries, and test the hypothesis \nthrough the statistical technique of meta-analysis. The results show that the country where the companies \nare home-based moderates the relationship between CSR and FP. In particular from the results, we can \nconclude that while in Australia, Canada, USA and the United Kingdom the relationship is stronger and \nlarger, in some countries, such as Japan, there is no relationship.
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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 | 0.000 | 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 | 0.001 | 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) | 0.035 | 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".