What Drives Investor Response to CSR Performance Reports?
Bibliographic record
Abstract
ABSTRACT Recent research finds that investors' assessments of a stock's fundamental value are influenced by corporate social responsibility (CSR) performance through the affect‐as‐information heuristic. We extend prior research by examining two boundary conditions for the use of this heuristic: (i) whether the CSR performance relates to activities that are integrated in a firm's core business practices (material CSR issues) or not (immaterial CSR issues), and (ii) whether the CSR performance is positive or negative. Employing an experimental method, we find that the affect‐as‐information heuristic applies only to immaterial CSR issues but not to material CSR issues, and only to positive but not negative CSR performance. Our findings suggest that investors likely use a heuristic approach to process immaterial and positive CSR issues, and a more deliberate and systematic approach to process material or negative CSR issues. Our study has both practical and theoretical implications.
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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 | 0.022 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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".