Empathetic Leadership: Motivating Organizational Citizenship Behavior and Strengthen Leader-Member Exchange Relationships
Bibliographic record
Abstract
Empathetic leadership can motivate employees to become more productive and improve job satisfaction. Motivation is a self-initiated behavior that influences organizational citizenship behavior. However, empathy remains a vague psychological construct that requires research into different forms of empathy. This study applied illocutionary (empathetic) speech to determine the ability to predict organizational citizenship behavior in the leader-member exchange relationship. Additionally, locutionary (meaning-making) and perlocutionary (direction-giving) speech was introduced to establish factors that may strengthen that relationship. The study consisted of three hundred nine full-time employees and revealed that illocutionary (empathetic) speech significantly predicted organizational citizenship behavior. Locutionary (meaning-making) and perlocutionary (direction-giving) speech strengthened that relationship and are consistent with felicity conditions. Therefore, leaders, managers, and supervisors should attend workshops or executive coaching to develop communication strategies based on empathetic, direction-giving, and meaning-making speech to motivate employee organizational citizenship in leader-member exchange relationships.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads 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".