Simulation Research on the Infection of Unsafe Behavior of Employees Based on Social Network
Bibliographic record
Abstract
In order to study the characteristics of unsafe behavior contagion, based on the small world network, an unsafe behavior contagion model with behavioral rules such as homogenization aggregation, second-degree relationship distance of infection, influence paradox, and attenuation of behavioral contagion was constructed. The Netlogo platform was used for simulation. According to the results, it is found that the transmission of unsafe behavior has the contagion characteristics of hysteresis, emerging, and progressiveness. Whether the contagion behaviors occur was determined by the average path length of the network. The strong connection relationship in the network structure would trigger the infection of unsafe behavior. There was a significant positive correlation between the node distribution level of the network structure and the time-consuming cycle of unsafe behavior. Through research and exploration of the formation law and diffusion characteristics of unsafe behaviors in social networks, it is expected to provide theoretical support and direction guidance for the prevention and control of unsafe behaviors in social networks, thereby promoting the improvement of individual and organizational safety performance.
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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 | 0.002 | 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 | 0.000 | 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) | 0.000 | 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".