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Record W1552801589 · doi:10.19173/irrodl.v14i4.1582

Leader-member exchange theory in higher and distance education

2013· article· en· W1552801589 on OpenAlexvenueno aff
Robert Power

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipOrganizational citizenship behaviorPsychologySocial psychologyAutonomyQuality (philosophy)Social exchange theorySocial identity theoryPublic relationsOrganizational commitmentPolitical scienceSocial groupEpistemology

Abstract

fetched live from OpenAlex

Unlike many other prominent leadership theories, leader-member exchange (LMX) theory does not focus on the specific characteristics of an effective organizational leader. Rather, LMX focuses on the nature and quality of the relationships between a leader and his or her individual subordinates. The ideal is for a leader to develop as many high-quality relationships as possible. This will lead to increases in subordinates’ sense of job satisfaction and organizational citizenship, as well as to increased productivity and attainment of organizational goals. LMX has been criticized for its potential to alienate some subordinates, failing to account for the effects of group dynamics and social identity, and failing to provide specific advice on how leaders can develop high-quality relationships. However, LMX has been heralded as an important leadership theory in higher and distance educational contexts because of its emphasis on promoting autonomy and citizenship, as well as its ability to complement and mediate transformational leadership styles. Recent authors have attempted to provide specific advice for leaders who want to learn how to build and capitalize on the high-quality relationships described by LMX theory.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.118
GPT teacher head0.382
Teacher spread0.264 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations34
Published2013
Admission routes1
Has abstractyes

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