Promoting Leadership Effectiveness in Organizations: A Case Study on the Involved Factors of Servant Leadership
Bibliographic record
Abstract
The world is crying out for ethical and effective leadership that serves others, invests in their development and fulfills a shared vision. Among the many leadership styles (i.e., authoritarian, benevolent dictatorship, participatory, etc.) the one that best represents the ideals embodied in the human factor is servant-leadership. Servant-leadership incorporates the ideals of empowerment, total quality, team building, and participatory management, and the service ethic into a leadership philosophy. This model of leadership emphasizes increased service to others; a holistic approach to work; promoting a sense of community; and the sharing of power in decision making. Servant-leaders must be value- and character-driven people who are performance and process oriented. The aim of this paper is determining the drivers of servant leadership in order to put servanthood behaviors activities into practice among leaders. So at first we developed literature on servant leadership. Then Thirty-three measurement items were developed on the basis of opinions from leaders and the literature. Then Data collection occurred via a questionnaire. To validate the measurement scales for servant leadership, we performed a factor analysis. The results show that a six-factor measurement model (including emotional dimension, commitment to community, egalitarianism, altruism, managerial skills and human skills) fits the data acceptably. All of the measurement items significantly loaded on the constructs on which they were hypothesized to load. These results gave us confidence that the measures are indeed valid and reliable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".