Managing Social and Environmental Disclosure Under Pressure: Distortions and Legitimacy Risks
Bibliographic record
Abstract
Sustainability disclosure has become a central component of corporate governance, yet it remains an area marked by ambiguity, uneven standards and growing institutional pressure. Firms are increasingly required to provide information that is complete, credible and defensible, but internal capabilities often lag behind expanding regulatory and stakeholder expectations. This misalignment creates a structural tension in which sustainability disclosure becomes a strategic act shaped by uncertainty, managerial interpretation and institutional dynamics.Drawing on institutional theory, legitimacy theory and research on corporate transparency, this article develops a conceptual framework to explain why and when organizations distort sustainability disclosure through overstatement or understatement. The analysis identifies three structural drivers of distortion—regulatory uncertainty, heterogeneous stakeholder scrutiny and gaps in internal reporting capabilities—and examines how managerial sensemaking influences whether disclosure is interpreted as an opportunity or a risk. The European Union serves as an illustrative case to show how dense and evolving regulation can heighten, rather than reduce, interpretive ambiguity.By offering a clearer understanding of the mechanisms behind sustainability disclosure distortion, the article contributes to strategic management research in two ways. First, it clarifies the institutional and organizational dynamics that shape sustainability reporting. Second, it identifies the conditions under which firms are more likely to produce balanced, credible and auditable sustainability disclosure. In a context where the demand for transparency is rising, understanding these dynamics is essential for sustaining legitimacy and improving the quality of sustainability information.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".