Overselling corporate social responsibility
Bibliographic record
Abstract
Abstract We show that firms hype up their corporate social responsibility (CSR) narratives during the turn‐of‐the‐year earnings conference calls to project an overly responsible public image of their firms. This previously unexplored phenomenon does not appear to be related to past, current, and future CSR engagements and cannot be explained by observed time‐varying firm attributes and unobserved time‐invariant firm and CEO attributes. We find that the fourth‐quarter CSR narrative hike is more pronounced among firms that are (ex ante) expected to do more corporate good as well as firms embedded in dirty industries, but less prevalent among firms facing elevated product‐market threats. Although elevated CSR narrative is associated with positive short‐term market reaction and lower near‐term stock price crash risk, such behavior tends to reduce financial report readability and leads to lower equity valuation in the longer term. Our analyses suggest that CSR narrative hike at the turn‐of‐the‐year is a pervasive phenomenon in the corporate landscape and may have valuation and governance implications.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".