Determining Specialties of the Jordanian Court of Cassation in Its Civil Capacity (According to Reality and the Law)
Bibliographic record
Abstract
The main objective of this research is to address the issue determining specialties of the Jordanian court of cassation according to reality and the law. To achieve this objective, the analytical comparative research design method is used depending on the legal legislations and the diligence of the Judiciary to remove ambiguity form them because of their importance and direct effect in determining specialty of court of cassation and to distinguish it from court of subject. This research is divided into two subjects: The essence of reality and essence of the law. The second topic has addressed specialty of court of cassation according to reality and the law, divided into two requirements: considering court of cassation as the upper Judicial body, and the second requirement about considering court of subject third degree of the Jurisdiction degrees. The research reached the presence of contradictions making it difficult to determine and to set a specific standard and the decisive line between what is reality and what is law. Based on the results, it is recommended the necessity for in-depth review and amendment of these two laws, setting independent legal texts for the civil trials principal law, organizing the Judges' authority technically to separate between reality and the law.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".