The Analysis of Administrators and Staffs Attitude from the Obstacles of Delegation of Authority
Bibliographic record
Abstract
This study was conducted to analyze the managers’ and employees’ attitude towards obstacles to devolutionin Mazandaran Province Gas Company (Iran). According to the exploratory studies, devolutionobstacles was explored and identified at two dimensions including managers’ unwillingness to devolutionand subordinates’ reluctance to accept authority. To analyze the data and to confirm or reject the research questions, first, the Kolmogorov-Smirnov test was used to determine the normality of data. Given the non-normality of data, non-parametric tests such as one-sample one-tailed Wilcoxon test, Friedman test for ranking components, and Mann–Whitney test were used to identify the employees’ and managers’ different perception of obstacles to delegation of authority. Findings of the study indicated that Wilcoxon test was not significant at o.o5; that is, lack of trust and confidence in subordinates, inability of managers in guiding subordinates, lack of controlling processes, managers’ sense of insecurity, and unwillingness of managers to delegate authority were not the main obstacles to devolutionby managers in Mazandran Province Gas Company, and their effects were not significant. In line with examining the obstacles effective to the devolutionby subordinates, it was found that the fear of criticism, blame, and dismissal along with the lack of adequate motivation in subordinates were recognized as the most important obstacles to adoption of authority by subordinates in Mazandran Province Gas Company.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".