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Record W2972096725 · doi:10.1080/13603124.2019.1657591

Exploring leadership-as-practice in the study of rural school leadership

2019· article· en· W2972096725 on OpenAlexaff
Tenneisha Nelson

Bibliographic record

VenueInternational Journal of Leadership in Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEducational leadershipLeadership stylePhenomenonLeadershipShared leadershipLeadership studiesNeuroleadershipTransactional leadershipServant leadershipSociologyValue (mathematics)Instructional leadershipPublic relationsPedagogyPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

This paper explores the value of using a practice lens to explore how leadership happens in a rural school. I contend that examining leadership-as-practice provides an alternate means of understanding the phenomenon of rural school leadership, which transitions the focus of study away from the traits and behaviors of individual school leaders, by providing insight into how leadership unfolds, as school actors work together. To advance this argument, I provide an overview of traditional approaches to studying leadership, and identify some of the drawbacks of these approaches. Drawing on the turn to practice in social theory as a reference point, I then draw attention to the study of leadership as a socially constructed phenomenon and use an illustrative case to demonstrate the value of a leadership-as practice lens. An overview of the methodological implications of studying leadership-as-practice is provided, with attention being paid to its potential to expand the focus of rural school leadership studies.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.016
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0020.002
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 head0.535
GPT teacher head0.460
Teacher spread0.075 · 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 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

Citations12
Published2019
Admission routes1
Has abstractyes

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