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Record W4225755158 · doi:10.7202/1085567ar

A Meta-Review of Servant Leadership: Construct, Correlates, and the Process

2022· article· en· W4225755158 on OpenAlexvenueno aff
Anjali Chaudhry, Xiaoyun Cao, Robert C. Liden, Sébastien Point, Prajya Rakshit Vidyarthi

Bibliographic record

VenueJournal of Comparative International Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsServant leadershipTransformational leadershipConstruct (python library)PsychologyRelevance (law)Social psychologyProcess (computing)ManagementSociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The goal of this article is to present qualitative and quantitative reviews of servant leadership literature since its formal inception in 1970. Summarizing previous studies, we theorized and explored issues concerning the conception and relevance of servant leadership, the merits of varied measurements, issues concerning construct dimensionality, and the potential effects of national culture on the relationship between servant leadership and its correlates. We developed theory to distinguish servant leadership from competing leadership theories of transformational leadership and leader-member exchange (LMX) theory and examined the direct and the incremental influence of servant leadership on individual and unit-level outcomes. To consolidate extant research and to guide future theory development we tested a mediational process model linking servant leadership to outcomes. Meta-analytic results supported distinctiveness of servant leadership, showed effects of servant leadership on individual-level and unit-level outcomes, and supported theorized mediating effects of trust and fairness perceptions in the relationship.

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 imitation

Not 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.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.088
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0180.016
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.302
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2022
Admission routes1
Has abstractyes

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