Does Corporate Governance Impact Corporate Social Responsibility Activities?
Bibliographic record
Abstract
Abstract Corporate social responsibility (CSR) can directly impact a corporation’s reputation. This impact in reputation affects the recognition and group awareness of different types of stakeholders and can have a significant positive impact on corporate performance. Through this research we aim to identify the link between corporate governance and CSR. Regarding the methodology, the data was processed using the Stata 15 program. We plotted the results using the GMM system. The research sample is a group of 532 European public companies. We took into account a period of analysis between 2014 to 2023. The main results of research capture a strong correlation between high corporate governance and engagement in CSR activities. Companies that are currently exempt from reporting ESG activities may find this research interesting. This paper can be useful for stakeholders (banking companies, investors, clients, the state). The participation of companies in social responsibility activities can be greatly beneficial for establishing trust between the company and stakeholders and can also strengthen the sense of responsibility of employees towards companies. Companies required to report under the Corporate Sustainability Reporting Directive: large listed and unlisted European companies that meet at least two of the following three criteria (Annual net turnover > EUR 40 million; Total assets > EUR 20 million; Average number of employees > 250); companies listed on regulated markets in the EU, including listed SMEs, but with some exemptions; non-EU companies that have operations in the EU and that meet the following criterion (Net turnover generated in the EU > EUR 150 million in at least two consecutive years); financial institutions, including banks and insurance companies, whether listed or not; Listed SMEs, with some exceptions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 source (direct Gemma or distilled Codex), 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".