Do organizational commitment and perceived discrimination matter? Effect of SR-HRM characteristics on employee's turnover intentions
Bibliographic record
Abstract
This study objectifies the linkage of Socially Responsible Human Resource Management (SRHRM) and turnover intentions of employees and/or staff.This is followed by measuring the mediating effects of perceived discrimination as well as organizational commitment on the aforementioned relationship.In this research, a sample of 310 employees were selected from 5 different hotels (5-star) located in Kyrenia, North Cyprus.Comparative studies have shown results that indicates a positive, and direct relationship between the two major variables of this study.The results of this research are in consensus with previous measures conducted upon the matter.According to the findings of this study SRHRM practices can decrease the intention of employees for quitting their jobs.In addition, organizational commitment affects their perception towards the organization, which in turn will lead in a lower level of turnover intentions.Perceived discrimination has been found to have effects on employees' commitment and performance.The lower the level of discrimination, and the higher level of proper SR-HRM practices and their implementation, the more commitment is engaged from the employees and the less intention towards leaving their job is apparent.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".