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Record W7155076934 · doi:10.59236/ijea15n4

Inspiring Creativity in Urban School Leaders

2014· article· W7155076934 on OpenAlexfundno aff
Girija Kaimal, Jon Drescher, Holly Fairbank, Adele Gonzaga, George P. White

Bibliographic record

VenueInternational journal of education and the arts · 2014
Typearticle
Language
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
FundersAteneo de Manila UniversityYork UniversityLehigh UniversityDrexel UniversityU.S. Department of EducationCity University of New YorkTemple University
KeywordsCreativityExperiential learningThe artsNarrativeGrounded theoryVisual arts educationEducational leadershipPrincipal (computer security)Narrative inquiryQualitative research

Abstract

fetched live from OpenAlex

This paper presents an analysis of how guided engagement with the arts can provide leadership lessons for school leaders and administrators. The study was conducted as part of two projects funded by the School Leadership Program (SLP) grants from the U.S. Department of Education. The principal interns and practicing school leaders participated in arts engagement activities (jazz ensemble, chamber orchestra, and tango dance) facilitated by teaching artists from the Maxine Green Center for Aesthetic Education and Social Imagination. Participants attended experiential workshops with teaching artists, observed the art form and then listened to the process and techniques used by the artists. Data sources for the study included observations, reflective narratives and interviews with participants. These were analyzed using grounded theory methods. The findings indicate that guided engagement with the arts provide lessons to school leaders in the form of interdisciplinary analogies and metaphors. The narratives generated by artists and participants served as a bridge: building connections between leadership and artistic practice. The experience encouraged participants to: gain new perspectives on optimal contexts for learning, develop a nuanced understanding of leadership, move from abstract to concrete understanding of relational constructs, and feel empowered through trying new experiences. Implications of the findings, including translating the lessons into actual practice and the addressing the needs of participants who did not connect with the sessions, are also discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.308
Teacher spread0.275 · 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.

Study designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

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