ANALYSIS OF HEALTH WORKERS' PRACTICE NEGLIGENCE: REVIEW OF ETHICAL CODES AND LEGAL ASPECTS
Bibliographic record
Abstract
Background. Healthcare professionals hold a unique ethical and legal responsibility for patient health, where negligence is considered a failure to maintain professional standards that can result in patient harm, leading to both ethical concerns and legal consequences. This study aimed to analyze health workers’ practice negligence to clarify ethical codes and legal concepts. Research method. This approach emphasizes review articles and normative studies, viewing law as a collection of written norms found in legislation, jurisprudence, and expert opinions. The study aims to conduct a normative analysis of the current, formally applicable legal framework, utilizing a statutory method to examine Law Number 17 of 2023, Law Number 29 of 2004, additional regulations from the Criminal Code, and relevant sectoral laws. Findings. The relationship between ethical norms and legal obligations in medical practice illustrates that ethical standards often precede legal frameworks by establishing professional expectations. Legal rules serve to enforce minimum care standards, protecting patients and practitioners. Negligence constitutes a breach of duty leading to harm, making health professionals liable under civil law for unlawful acts causing injury, thereby allowing patients to seek compensation. In Indonesia, health law defines legal obligations and penalties for negligence, with civil and criminal liabilities relevant in severe injury or death cases. Conclusion. The importance of clarity in legal standards to adjudicate malpractice claims. A key harmonization, when ethical and legal systems diverge, conflicts can arise, for instance, between respecting autonomy and mandated interventions. Ethical guidelines can help resolve these tensions, but cannot substitute for legal accountability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.012 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".