The Influence of Corporate Social Responsibility Measures on Investors' Judgments when Integrated in a Financial Report versus Presented in a Separate Report
Bibliographic record
Abstract
ABSTRACT This study examines the effect on investors' judgments of corporate social responsibility (CSR) measures when integrated with financial information in a single report versus when presented in a separate CSR report. Advocates for integrated reports argue that CSR information will be perceived as more relevant and have a greater impact on users when observed in an integrated report. However, we provide experimental evidence that CSR measures have greater influence on investors' judgments when investors observe the CSR information and financial information depicted in separate reports. We also provide evidence that this greater influence of CSR measures is caused by investors' evaluations taking on a “multidimensional perspective” that includes both a social responsibility and a financial dimension, which is triggered by observing the separate CSR report. Activating a social responsibility dimension elevates the perceived relevance of CSR measures, increasing their influence on investors' judgments. Our study contributes to practice by highlighting a potential unintended consequence of issuing integrated versus separate CSR reports: that investors incorporate CSR information less when it is integrated with financial information versus separately reported.
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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 | 0.009 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".