Toxic Decision Processes: A Study of Emotion and Organizational Decision Making
Why this work is in the frame
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Bibliographic record
Abstract
This paper addresses the role of emotion in organizational decision making. Grounding our research in the decision process literature, we introduce the concept of “toxic decision processes”: organizational decision processes that generate widespread negative emotion in an organization through the recursive interplay of members' actions and negative emotions. We draw on a longitudinal, qualitative analysis of six toxic decision processes to develop a model that describes the three phases—inertia, detonation, and containment—through which these processes unfold. Each phase is characterized by distinctive sets of interactions among decision makers and other organizational members, and by emotions such as anxiety, fear, shame, anger, and embarrassment, that shape and are shaped by these interactions. We show that toxic decision processes are triggered by issues that are sensitive, ambiguous, and nonurgent and identify several mechanisms that connect actors' emotions and actions, over time creating a toxic decision process that leads to the cumulative buildup and diffusion of toxicity. These mechanisms include the construction of a “danger zone” around the issue that is avoided by all parties, the spread of negative emotion through processes of empathetic transmission and emotional contagion, and the suppression of widespread negative emotion that leads to the development of a volatile emotional context for future decision making. This study has important implications for the decision process literature, revealing how the different lenses through which decision making is usually viewed are connected by the emotionality that runs through each of them.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it