When caring breeds contempt: The impact of moral emotions on healthcare professionals’ commitment during a pandemic
Why this work is in the frame
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Bibliographic record
Abstract
The novel coronavirus (COVID-19) pandemic is a major heath crisis that continues to impact healthcare organizations worldwide. As infection rates surged, there was a global shortage of personal protective equipment, critical medications, ventilators, and hospital beds, meaning that healthcare professionals faced increasingly difficult workplace conditions. In this conceptual study, we argue these situations can lead to healthcare professionals experiencing moral emotions - defined as specific emotions which relate, or occur in response, to the interest or welfare of others - towards their organizations. This paper explores the three moral emotions of contempt, anger and disgust, and their potential influence on healthcare professionals' workplace commitment in the context of a pandemic. Drawing from the moral emotions and organizational commitment literature, we develop a process model to demonstrate how healthcare professionals' affective and continuous commitment are likely to decrease while, paradoxically, normative, and professional commitment may become amplified. The possible potential for positive outcomes from negative moral emotions is discussed, followed by theoretical and practical contributions of the model, and finally, directions for future research.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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