How Can Servant Leaders Foster Public Employees’ Service‐Oriented Behaviors? A Multilevel Multisource Study in Canadian Libraries
Bibliographic record
Abstract
Abstract Servant leadership, a leadership style that focuses on leading by serving, is well suited to supporting frontline employees’ service‐oriented behaviors in the public sector. However, we still know little about how servant leaders shape these behaviors in this specific context. Drawing on social learning theory, relational identity, and service linkage research, this article addresses this gap and tests a model in which servant leadership is related to service‐oriented behaviors through customer orientation at the individual level and through service climate at the group level. The research hypotheses were tested, using a multilevel model, on a sample of 922 employees, 86 supervisors, and 9,547 citizens nested in 86 Canadian libraries. Results show that servant leaders are associated with high service‐oriented behaviors through the ability to strengthen individual customer orientation and service climate. Overall, this article highlights that developing servant leaders may help public organizations reach their goal of serving citizens better.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".