Investigating important factors on empowering human resources: A case study of food industry
Bibliographic record
Abstract
Today, human resources are considered as the most precious assets for any organization and it is important to empower them as much as possible to create competitive advantage and to cope with rapid changes in organizations. In this paper, we present an empirical study on one of food industries in province of Qom, Iran to determine important factors influencing empowering human resources. The proposed study uses factor analysis by choosing a sample of 380 people. Cronbach alpha is calculated as 0.88, which is well above the minimum acceptable limit of 0.7 and validates the overall questionnaire. Based on the results of this survey, there are three important factors including job related, personal related and organizational related issues. The study also uses Pearson correlation as well as Freedman tests to rank the factors and the results demonstrate that organizational factor plays the most important role in empowering human resources followed by job related factors and personal factors.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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".