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Record W7155751803

The Influence of Adaptive Schools Training on the Development of Principals' Leadership Identity

2022· dissertation· en· W7155751803 on OpenAlexaboutno aff
Lucinda Wolters

Bibliographic record

VenueKU ScholarWorks (The University of Kansas) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYIdentity (music)Training (meteorology)Qualitative researchShared leadershipLeadership developmentLeadership styleEducational leadership
DOInot available

Abstract

fetched live from OpenAlex

Leadership identity is currently viewed as a capacity precursor and necessary for principals to effectively lead learning in schools during today’s complex times. This study investigated the influence of Adaptive School (AS) training on the development of principals’ leadership identity. Through a basic interpretive qualitative approach, interviews took place with 12 North American public-school principals from elementary, secondary, or blended schools. Through semi-structured interviews, the principals shared their experiences and how they used what they learned in response to the AS training. The themes from the research revealed that the AS training had a clear influence on these principals’ leadership identity. They highly valued the training and found it helpful, and applicable to their leadership. In addition, they found the training format to be useful in providing clarity on how to facilitate learning in their schools, as a “leader for learning.” Seven of the participants described the AS training as transformative. Others relayed how it provided clarity for how to enact their already well-defined leadership identities. The principals used what they learned in meetings; in particular, they applied norms of collaboration, dialogue, and discussion structures in their schools after the AS training. They found understanding the concept of complex adaptive systems (CAS) helpful to manage complexity and uncertainty by being more calm, open, objective, and responsive. Some principals noted areas for development within the organization, Thinking Collaborative, in particular, the need for further racial equality, Canadian accessibility, and adaptivity in a pandemic.

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)0.014
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.005
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
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 head0.187
GPT teacher head0.348
Teacher spread0.161 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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