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Measuring Servant Leadership

2014· book-chapter· en· W2349345233 on OpenAlexaff
Claudio Pousa

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2014
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsLakehead University
Fundersnot available
KeywordsServant leadershipConstruct (python library)Set (abstract data type)ServantMeasure (data warehouse)PsychologyPolitical scienceEpistemologyComputer sciencePublic relationsLeadership stylePhilosophySoftware engineeringData mining

Abstract

fetched live from OpenAlex

The concept of Servant Leadership was introduced by Robert Greenleaf in the 1970s, and although in his works there is a very clear picture of servant leadership in philosophical terms, there is not an empirically validated definition of servant leadership. For this reason, numerous scholars worked individually on developing competing frameworks to define servant leadership since the mid-1990s; the result is that, throughout the scientific literature, the construct of servant leadership is defined by an inconsistent set of dimensions and there is still no consensus about an operational definition of the construct. In a similar way, since the end of the 1990s, numerous scholars developed different scales to measure servant leadership, based on different operational definitions. Accordingly, there is not an agreed upon measure of Servant Leadership; a few measures were used in a limited number of studies, and a relatively large number of measures were used in less than two. The chapter presents the most significant and used operational definitions, a detailed description of the development of the different measuring instruments, as well as a reference to some of the studies that used them, and a final section where the advantages and disadvantages of using certain measures are presented.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.205
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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