Servant leadership theory in practice: North America’s leading public libraries
Bibliographic record
Abstract
This study aims to understand the current North American public library directors’ views and perceptions of successful library leadership in the 21st century. It was carried out based around a series of semi-structured interviews with 10 top-level directors of public libraries in the United States and Canada, which were published in the book World’s Leading National, Public, Monastery and Royal Library Directors: Leadership, Management: Future of Libraries. The data collection method for this study consisted of narrative analysis of the 10 interviews utilizing Robert Greenleaf’s servant leadership theory, which highlights the leader’s desire to serve others first and foremost. With the current trends of increased globalization, digitization, and cultural diversity, among others, public libraries need to have leadership focused on creating shared-power environments encouraging collaboration. Analysis of these interviews showed that many of the directors’ responses were quite similar to the concepts discussed in servant leadership. The library directors, through their leadership philosophies, benefited in boosting team cohesion, fostering collaboration, increasing creativity, and promoting morality-centered self-reflection amongst leaders, thereby helping their libraries gain and maintain competitive advantage, and improving the overall ethical culture of their organizations. The results of this study would be of interest to library professionals interested in management as well as LIS students who want to understand how library directors view successful traits of library leadership.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".