The Impact of Social Responsibility Disclosure on Corporate Financial Health: Evidences from Some Italian Public Companies
Bibliographic record
Abstract
Companies are today often seen as one actor in a complex system linking all the actors with several, different ties, and binding them by a social contract asking each of them to meet the expectations of the other social actors in the same context, in order to get the legitimacy they need. Corporations can adopt social disclosure to increase their legitimacy towards all stakeholders, influencing their behavior and leading to the creation of a positive Corporate Association (Brown and Dacin, 1997). In this paper we investigate the relationship between Social Responsibility Disclosure practices and Corporate Performance. We develop a framework to study this topic through several perspectives: External evaluation (Ethical Ratings), utilization of specific behaviors (Ethical Labels), Principle (Code of Ethics) and Behaviors (Social Reports) disclosure. In order to get a first understanding of these relationships we have selected a sample of Italian Companies listed on the italian stock exchange.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".