From Voice to Action? A Survey on Organizational and Individual Factors Impacting Employee Activism Intentions
Bibliographic record
Abstract
Activism is increasingly shaping social and political arenas and influencing the corporate world. This study examines the factors that drive employee activism within organizations, focusing on how organizational and individual factors influence both communicative and actionable activism intentions. Drawing on a survey of 324 Italian public and private sector employees, we investigate the impact of: (a) organizational factors, specifically climate of voice, transparent leadership communication, and perceived corporate authenticity; and (b) individual factors, specifically perceived external prestige, organizational identification, and employee engagement. Additionally, we explore the moderating role of (c) corporate and CEO activism, as leaders’ active involvement in social, political, and environmental issues may influence employee activism intentions. Findings underscore that a supportive voice climate, authentic alignment of corporate values, and transparent leadership communication empower employees toward activism. This study provides strategic implications for integrating purpose-driven values into internal communication and leadership practices to cultivate an organizational culture that encourages proactive employee engagement and advocacy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".