Vote the Assholes Out: How Value Congruence Work Aligns Stakeholders for Corporate Activism
Bibliographic record
Abstract
As more firms take stands on contentious social issues, research has pointed to alignment between the values of a firm and its stakeholders as a key driver of this corporate activism. However, this “stakeholder alignment” model of corporate activism has not offered insights into how the values of a firm and its stakeholders become and remain aligned. Drawing from an inductive study of Patagonia, Inc., we introduce the concept of value congruence work — the purposeful efforts of firms to align the values of stakeholders with their own — as a central activity for firms engaging in corporate activism. Our analysis highlights two forms of value congruence work: attractional value congruence work serves to draw in stakeholders with aligned values to engage with the firm, and co-evolutionary value congruence work serves to grow and enhance value congruence over time through different forms of learning. Our findings offer new insights for research on corporate activism and social-symbolic work.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".