The Relationship between Servant Leadership, Organizational Citizenship Behaviour, and Dysfunctional Turnover
Bibliographic record
Abstract
The purpose of this conceptual paper is to provide a framework to enhance the understanding of factors that influence the turnover rate among high performers in an organization. The focus of this proposed conceptual framework is the study of the relationship between leadership style, organizational citizenship behaviour, and dysfunctional turnover. Based on literature reviews, evidences reveal a negative relationship between servant leadership and dysfunctional turnover which is mediated by the variable of organizational citizenship behaviour. From a practical standpoint, this paper provides additional knowledge in the area of dysfunctional turnover which can assist the relevant stakeholders in an organization to reduce brain drain and enable HR practitioners to have a better understanding on how to reduce turnover rate among high performers; whilst at the same time, contributing to the existing number of valuable researches that provide the much-needed knowledge in understanding the turnover phenomenon. Hence, there is a need to conduct an empirical based study to validate the proposed conceptual framework and to ascertain the relationship among the various variables in this framework.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".