The Impact of Corona Pandemic on Legal Protection of Jordanian Employee's Right to Salary and Its Extensions
Bibliographic record
Abstract
The topic of the study is of special importance, as it relates to the source of public employee income and contemplates unusual events imposed by the Corona pandemic; Led to multiple preventive measures being taken to counter them; including the validity of the emergency defense law, which has multiple effects at all levels. To address negative economic conditions, administrative decisions were issued by the Cabinet against employees, which led to a reduction in their salaries and benefits. Hence, the study problem arose. Because it was not issued by the authority specified by the Defense Law which gives this authority to the Prime Minster, and accordingly many decisions exceeded its established legal rules and specific constitutional texts. The study aims to shit light on many aspects pertaining to the legal protection of Jordanian employee's right to salary and the basis on which the administration can modify it? We reached a set of results, most notably: The validity of the Defense Law specifically gives the Prime Minister, and not the Cabinet, the power to take exceptional measures to face the exceptional circumstance, by invoking exceptional legal rules stipulated by this law and not on the ground of the Civil Service Regulation. The most important recommendation was to cancel the new amendment of Article (193) of the Civil Service Regulation in line with the rule of legislative progression, as it contradicts the defense law and constitutes a violation of the constitutional provisions.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".