Contagion risk: How stakeholders mediate the impact of rivals’ misfortunes on firms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to investigate the dynamics of contagion and its impact on firms, specifically focusing on how a rival’s failure to control an event can have adverse consequences for other firms. Through a comprehensive analysis of relevant theories, literature, and real-world cases, the study identifies key factors that contribute to the contagion process and proposes a framework for assessing the associated risk. The research highlights the crucial role of stakeholders in mediating the effects of rivals’ misfortunes on other firms and emphasizes how stakeholders’ identities shape their risk evaluations, thereby affecting the occurrence of contagion. This study contributes to the existing literature by providing a conceptualization of the contagion process and introducing the concept of “stakeholder identity” within the context of organizational and operational risk management. The findings offer practical insights to firms by emphasizing the significance of contagion risk, which is often overlooked in operational risk management strategies. Additionally, the study provides valuable guidance on how firms can effectively assess their vulnerability to contagion, enabling them to proactively manage and mitigate their risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it