The Liability of the Custodian If the Victim is Proven to Have Contributed to the Damage
Bibliographic record
Abstract
Aims: This study aims to address the custodian liability for losses caused by an object under his control, especially for the damages occurred by mechanical machines, and showing the effect of split liability on the custodian’s liability especially in cases of paying compensation to the victim. On the other hand, this study discusses the custodian liability under the Jordanian law and some of the Arab laws. Materials and methods: Following identification of the study objectives, the researcher compared the legal frames in Jordan and other surrounding countries. The researcher was able to formulate the present study. Study findings: The legal text in Article (261) of the Jordanian Civil Code exempts the custodian in its main text from paying compensation under some conditions such as natural disaster, unavoidable accident, force majeure, an act of a third party, or act of the person suffering loss, while at the same time the Article ended with the phrase “unless otherwise stipulated by law or agreement.” Which I think is unnecessary here and shall be omitted. The Jordanian legislation also neglected to clarify the types of fault that may be caused by the victim especially, if it is proved that the victim has contributed to causing the damage, the fault of the custodian, in this case, can be rebutted. Conclusion: The Jordanian legislator did not comprehensively specify the types of the victim’s fault, while the Lebanese legislator has clarified those types. Explicitly, there is no need for the part of Article (261) of the Jordanian Civil Law which says that "otherwise or agreement" because the text is clear and fulfills its intended purpose.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".