Fight Alone or Together? The Influence of Risk Perception on Helping Behavior
Bibliographic record
Abstract
Will there be a greater sense of solidarity and friendship during public crises? This study aims to determine whether risk perception influences employees’ willingness to assist in times of public crisis, taking COVID-19 as a specific research scenario and based on the theory of “tend and befriend”. This study hypothesized that risk perception will influence employees’ helping behavior via the in-group identity, with the degree of impact dependent on the COVID-19 pandemic’s severity. A questionnaire survey of 925 practitioners from various industries in the pandemic area revealed that: risk perception has a positive influence on employees’ helping behavior; in-group identity plays a certain mediating role in the process of risk perception that influences employees’ helping behavior; and the severity of a local pandemic negatively moderates the relationship between risk perception and helping behavior, but positively moderates the relationship between risk perception and in-group identity. Specifically, employees in high-risk areas are more likely to “align” (higher degree of recognition by the in-group) but demonstrate less helping behavior, compared with those in areas with moderate and low risk from the COVID-19. By contrast, employees in low-risk areas display more helping behavior but have less in-group identity, compared with those in areas with moderate and high risk from the COVID-19. This study expands the research on the relationship between risk perception and helping behavior, enriches the research results on risk management theory, and provides a practical reference for risk governance.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".