The Impact of Talent Management on Resident Doctor Performance at Jordanian Ministry of Health Educational Hospitals
Bibliographic record
Abstract
This study aims to identify the impact of talent management on medical physician performance at the Jordan ministry of health educational hospitals. However, the population of study was the resident physicians at the three educational hospitals (Prince HAMZA, Princess BASMA and AL-Karak), and the number of population was (478) male and female doctors, and the study sample consisted of (77) male and female resident physicians at the educational hospitals, forming (16%) of the study population. On the other hand, the two researchers relied on the questionnaire in order to collect data on the study sample, and they relied on the descriptive approach and single and multiple regression to analyze the data. The results of study show the following: that the level of talent management application at the three educational hospitals came with moderate level, and the arithmetic mean for the estimates of sample individuals on resident doctors areas was moderate at large, also, there is a significant statistically impact at (α≤0.05) for the management of talents in its dimensions on the resident physician performance, but with moderate level, also there is impact of talent management on all physician performance dimensions (morning report presentation, doing morning round, examining and admitting the patients at night and evening shift and coordinating with other departments in hospital for diagnostic procedures).So, the study recommended that education hospitals should develop systems and programs to attract, select, develop, evaluate the talent and make available all tools necessary to retain talent physician and keep abreast with modern management thought in talent management practice at the educational Jordanian hospitals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".