A study on relationship between empowering employees and social capital depreciation: A case study of treasury department
Bibliographic record
Abstract
Empowering employee plays essential role in having sustainable social capital. When social capital is depreciated, we may expect some negative consequences on society and working environment. Therefore, we need to investigate different factors influencing depreciation of social capital as well as empowering employees. The proposed model of this paper designs a questionnaire and distributes it among some randomly selected employees who worked for treasury department in Iran. The study uses two regression models, where empowering employees is a function of four independent variables including being effective, having the right to select, competency and being meaningful. The other regression model studies the relationship between depreciation of employee as dependent variable and four independent variables including job involvement, television, living affairs and generation change. The results of both regression analyses indicate that there were some positive and meaningful relationship between empowering employees as well as depreciation of employees as dependent variable and independent variables.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".