Bibliographic record
Abstract
The aim of this reseach is to investigate the influence of transglobal leadership to the employees' performance with the Quality of Work Life mediation in koa malang, pasuruan and surabaya with the multigroup method as a more comprehensive form of the transglobal leadership to the improvement of the employees' performance, so that it is expected that it can explain the interdependence and generalization that are more complete than the previous research.The population in this research is all employees of The Most Outstanding Cooperatives in East Java Province.The Employees of The Most Outstanding Cooperatives in East Java Province as the research subject with the following considerations: (1) the employees are authorized to explain the things related to the research variables and (2) the employees are the frontliners of the organization and deal directly with members, customers, and surrounding communities.Based on data from the Department of Cooperatives and SMEs (2014), the number of employees as the population size in this research is 660 employees.The determination of the sample size was by using the Slovin's Formula in the precision of 5% with the following calculation obtained a sample of 249 people.The calculation in the sampling area is determined that 249 employees to be a sample taken from 25 The Most Outstanding Cooperatives based on the region.The analysis result shows that the four hypotheses in each area are acceptable.There is a significant direct influence among transglobal leadership and quality of work life (QWL) as well as employee's performance in Malang, Pasuruan, and Surabaya.Besides, there is a result of a significant positive influence of transglobal leadership to employee's performance through the mediation of quality of work life (QWL).From the coefficient values of the three areas, it can be identified that the highest influence of the transglobal leadership to the employee's performance through the mediation of quality of work life (QWL) is in Surabaya.The sequenses of discussion of variables in this research are that: 1) The variable Transglobal leadership (X1) is explained by the aspects of cognitive intelligece, emotional intelligence, business intelligence, cultural intelligence, global intelligence and moral intelligence, as described by Holt & Seki [2], Sharkey et al. [4] 2) Quality of work life is described from the aspects of participation, growth and development, compensation and work environment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.929 | 0.894 |
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".