The Impact of Social and Positive Psychological Capital on the Efficiency: A Field Study From the Perspective of Jordanian Auditors of the Performance of Audit Offices
Bibliographic record
Abstract
The main objective of this study is to show the social positive and psychological impact on the performance efficiency of audit offices from the perspective of the employees in those offices, and to fulfill this, the researchers relied on two inputs: the inductive and descriptive analytical approach, as well as relying on spss software to analyze data of this study, and test the hypothesis, which were in descriptive statistics metrics, model fit tests, and multiple linear regression analysis, to test the study hypothesis. The study sample consisted of 325 qualified people working in these offices. The most important conclusion from this research is that the psychological capital develops the fruitful exploitation of auditors in the work, to accomplish the audit work. In addition, the directors of audit offices seek to establish social cooperative relations among office workers. The most substantial recommendations of this research are crystallized by attracting human and intellectually, psychologically, socially and practically qualified elements who have sufficient skills and experience in auditing processes, in addition, the demand to encourage teamwork, and give powers to team members, so that many of the work problems are resolved through teams.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".