Bibliographic record
Abstract
The aim of this study was to determine civil liability arising from the exercise of employee and employer. The terms of realization of civil liability include the general and specific conditions and of important theories about civil liability of employers against workers is the risk and fault theory. The popular legal opinion is that employer's liability is based on the fault assumption which refers to a fault-based liability where the fault is assumed and doesn’t need proof. But it seems the base of sum of the employer's liability is sum and integration of risk theories and the fault assumption because in the fault assumption we see the individual’s assumed liability that he/she can proofing lack of fault or failure come out from liability burden. Despite the respect for civil rights doctrine, in the opinion of the writer (author) perhaps we can’t present a recorded and definite basis for employer's liability, as most lawyers believe. So what is in the law is the collective result of the integration fault assumption and derivatives of risk theory. In this study, conducted using descriptive – analytical, to identify the various intellectual foundations on raised issue, the Legal Opinions, law of common law and Romano-Germanic in this article are referred to different approaches on the issue ahead be explained.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".