Evaluation of the in-Service Training Courses Impact on Empowerment of National Iranian South Oilfields Company’s Employees
Bibliographic record
Abstract
Manpower training leads to development of their potential, promotion of work methods and techniques of work, knowledge acquisition and increased job skills and prevention of resource loss for the organization. This is a descriptive study which is carried out in April 2015 to evaluate the effect of in-service training courses on employee empowerment among National Iranian South Oilfields Company (NISOC) employee in the years 2012-2014. A sample size of 148 employees was randomly selected from the population of the study, and standard questionnaires of leadership power, organizational commitment by Allen Meyer and average of the employee in specialized training courses were used for data collection. Descriptive and inferential statistics, frequency, mean, standard deviation, one way ANOVA, independent t-test, analysis of variance (ANOVA) were measured in statistical software of SPSS 21 for data analysis. The results showed that training courses have been effective in empowerment (leadership, organizational commitment and expertise) of the employee. In addition, no significant difference was found between effectiveness of training courses and empowerment of employee expertise in different field of studys and universities. But there was a significant difference between effectiveness of training courses, and empowerment of employee expertise based on their level and type of education. Therefore, considering the effectiveness of in-service training courses on employee empowerment, there is a necessary need for serious planning for appropriate military establishments for optimal implementation of these programs,
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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".