Criminological Assessment of Medical Misconduct during the COVID-19 Pandemic
Bibliographic record
Abstract
This study examines the professional actions of health workers during the spread of the COVID-19 pandemic from the point of view of criminological assessment in the context of labor relations. With the help of political and legal analysis and a comparative legal method, the work considers the international practice of assessing the actions of medical workers from the standpoint of criminal responsibility, political and legal initiatives concerning the protection of the rights of medical workers during the spread of a pandemic and quarantine measures. This study argues for significantly broader criminal immunity for health workers during a pandemic. At the same time, the study gives grounds to assert that today the lack of sufficient empirical data and research complicates an objective assessment of the offender. At the same time, based on the results of this study, it is suggested that in the near future the number of investigations and appeals to the court on issues related to the professional activities of medical workers carried out during the spread of the pandemic will increase..
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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 | 0.004 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".