Does corporate governance affect corporate social responsibility?
Bibliographic record
Abstract
This research aimed to examine the impact of corporate governance on the corporate social responsibility of the Jordanian companies listed on the Amman stock exchange. Using a dynamic panel system, the current investigation of 65 Jordanians uses GMM estimation for the years 2018 to 2022. Corporate social responsibility has been measured using a corporate social responsibility index. It has 84 items divided into four groups: employee activity items, environmental items, objects related to society and the items related to customers are in the last group. The study concluded that Jordan demonstrated a substantial level of corporate social responsibility in keeping with Jordan's expanding understanding of and practice of corporate governance. Specifically, this study indicated that board meetings, foreign ownership, and block holder ownership significantly influenced corporate social responsibility. Our study’s findings should interest policymakers as well as regulators in nations with similar business ownership and regulatory regimes. This study contributes to addressing an oversight in the literature on social responsibility studies as well as corporate governance characteristics. As a result, this paper provides useful information and insights for businesses and regulators seeking to increase the impact of social responsibility on their businesses through a focus on corporate governance excellence.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".