Symbolic or substantive? How shareholder heterogeneity shapes the purpose of the corporation
Bibliographic record
Abstract
This study investigates how the heterogeneity of shareholders’ financial and social interests creates tension around competing interpretations of the purpose of the corporation, particularly regarding their incompatibility and relative prevalence of initiatives that extend beyond profit maximization. These tensions are especially salient when shareholder activists—who possess both legal rights and economic influence—exert divergent pressures to achieve both financial and social goals, which then shapes how firms respond to such pressures. Based on a sample of 5,302 shareholder-initiated proposals submitted to S&P 1500 firms, we find that when the variety of shareholders targeting a firm blends conflicting perspectives about pursuing profit and social goals to a greater extent, firms are more likely to respond with symbolic actions, for a consequential misalignment between advocated CSR policies and implemented practices. We also provide evidence that this association is weaker in the presence of activism and ownership by shareholders who publicly self-identify as socially oriented investors, suggesting that these investors influence both the credibility and the centrality of the social logic in managerial decision-making. Our results advance understanding of how firms navigate the complexities of achieving a purpose of the corporation beyond profit maximization, amid the evolving landscape of divergent shareholder interests and activism.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| 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".