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Record W2887578091 · doi:10.12806/v17/i3/r7

A Longitudinal Evaluation of Change Leadership within a Leadership Development Program Context

2018· article· en· W2887578091 on OpenAlexaff
Kevan W. Lamm, Lara Sapp, Alexa J. Lamm

Bibliographic record

VenueJournal of Leadership Education · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsBrandon University
Fundersnot available
KeywordsLeadership developmentEducational leadershipNeuroleadershipTransformational leadershipLeadership styleLeadership studiesContext (archaeology)Shared leadershipTransactional leadershipPolitical scienceLeadershipScale (ratio)Public relationsPsychologyPedagogyGeography

Abstract

fetched live from OpenAlex

The need for individuals capable of leading change has become pronounced based on the changes occurring within the higher education system. The purpose of this study was to examine if participation in the LEAD21 leadership development program, a national leadership program for faculty emerging as leaders in the land-grant university system, changed participant levels of change leadership. The longitudinal analysis included comparisons across members of three classes in the LEAD21 program, as well as the aggregated data from all three years. Results indicated overall level of change leadership rose by an average of 28.8%. Additionally, the study established benchmarks for pre-program and post-program levels of change leadership. Leadership educators can use the results to inform future leadership education initiatives. Furthermore, the study presents a Leading Change Scale that may be appropriate for future leadership program evaluations. Ongoing evaluations of leadership programs are encouraged.

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)0.014
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.450
GPT teacher head0.358
Teacher spread0.092 · 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 designObservational
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

Citations6
Published2018
Admission routes1
Has abstractyes

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