Activism for Corporate Responsibility: Conceptualizing Private Regulation Opportunity Structures
Bibliographic record
Abstract
Abstract In this article, we examine how private regulatory initiatives (PRIs) – which define standards for corporate responsibility (CR) issues and sometimes monitor their application by firms – create opportunities and constraints for activist groups aiming to push firms towards more stringent CR activities. Drawing on social movement theory, we conceptualize how private regulation opportunity structures affect such CR‐based activist groups' targets and tactics at both the firm and field levels. At the field level, we argue that both radical and reformative activist groups direct most of their time and resources towards PRIs with comparatively more stringent standards. At the firm level, while radical activist groups are likely to target firms participating in more stringent PRIs, reformative activist groups target firms participating in less stringent PRIs, or those that do not participate in PRIs at all. When facing unfavourable opportunity structures, CR‐based activist groups tend either to advocate the creation of new PRIs or to shift their activities to pressure other focal points. This article contributes to moving beyond extant literature's emphasis of PRIs as settlements of contentious firm–activist interactions towards also viewing them as starting points for activist groups aiming to push firms towards a more substantive CR engagement.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".