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Record W2601142525 · doi:10.22230/ijepl.2017v12n1a670

Developing Leadership Capacity in Others: An Examination of High School Principals' Personal Capacities for Fostering Leadership

2017· article· en· W2601142525 on OpenAlexvenueno aff
Kristin Shawn Huggins

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEducational leadershipLeadership developmentLeadership studiesShared leadershipLeadership stylePublic relationsServant leadershipCapacity buildingLeadershipPolitical scienceDistributed leadershipPsychologyPedagogy

Abstract

fetched live from OpenAlex

In this multisite case study, we examine the personal capacities of six high school principals who have developed the leadership capacities of other leaders in their respective schools. Participants were purposefully selected by two teams of researchers in two states of the United States, one on the east coast and one on the west coast, who engaged their professional networks of current and former educational leaders to obtain recommendations of high school principals known to develop the leadership capacities of formal and informal leaders in their schools. The findings indicate that the principals possessed a strong commitment to developing leadership capacity, understood leadership development as a process and tolerated risk. This study adds to the rapidly growing corpus of literature focused on distributed leaders by illustrating the complexities of developing leadership capacity in an attempt to increase organizational leadership capacity, and by highlighting the relevant characteristics of principals who have intentionally sought to do so.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.658
GPT teacher head0.466
Teacher spread0.191 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations24
Published2017
Admission routes1
Has abstractyes

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