Bibliographic record
Abstract
This study aimed to investigate the relationship between social intelligence of employees on customer satisfaction in Melli National Banks in Rafsanjan.The method has been descriptive-correlational, respectively.The study population included all the staff and customers of Melli Banks in Rafsanjan, numbered 173 People.Considering the number of employees due to the small population size and the number of customers using census method according to Cochran's formula, 384 people were randomly selected.To collect data from two standard questionnaires of social intelligence (2010) with 20 items with a validity of 94/0 and stability of 89/0 and standard questionnaire with 25 questions of customer satisfaction, Hashem Zadeh (2009) with a validity of 86/0 stability 83/0 were used.In order to analyze the data with software SPSS 19, the multivariate regression analysis and Pearson were used.The results showed that there is a significant relationship between employees with social intelligence and customer satisfaction.Considering social awareness among employees, social information processing and social skills, there is a significant positive relationship between employees and customer satisfaction.customer satisfaction is the most important predictor of social awareness and social skills.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.870 | 0.865 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".