More Money, More Ethical Commitment? How Corporate Financial Performance Influences Environmental Social and Governance Practices
Bibliographic record
Abstract
This article explores the relationship between corporate financial performance (CFP) and commitment to ESG (environmental, social and governance) practices, using a sample of companies listed on the S&P 500 and TSX 60 indices. By employing a linear regression model, the study examines how financial indicators such as Earnings Before Interest, Taxes, Depreciation and Amortization (EBITDA), return on assets (ROA), Assets and Debt influence ESG scores. The results show that financial indicators such as EBITDA, ROA and Assets are positively associated with increased ability to commit resources to ESG practices, except in some cases like when costs associated with ESG initiatives can reduce the competitiveness and profitability of companies in the short term, where ROA is negatively correlated with the adoption of ESG criteria. Also, with regard to the size of companies, thanks to their greater resources, larger companies are more inclined to adopt ESG criteria. These findings enhance the understanding of financial conditions that enable or constrain ESG adoption and provide managerial insights for strategic resource allocation in the pursuit of sustainability goals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".