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Enabling Transformational Complexity Leadership in Education

2023· book-chapter· en· W4386334844 on OpenAlexaff
Beryl Peters, Timothy Shawn Beyak

Bibliographic record

VenueAdvances in logistics, operations, and management science book series · 2023
Typebook-chapter
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTransformational leadershipTransformative learningAction (physics)Complex adaptive systemContext (archaeology)Shared leadershipTransactional leadershipEducational leadershipComplexity scienceLeadership studiesAction researchLeadership theorySociologyPublic relationsPolitical scienceEngineering ethicsLeadership stylePedagogyManagement scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

This chapter answers calls for a transformational, distributed, action-centered approach to leadership to engage with, problematize, and take action to address complexities and challenges facing education. Complexity leadership theory is informed by complexity theory, grounded in complex adaptive systems, and characterized by multi-level, dynamic interactions, and emergence. The authors describe ways that their formal and informal leadership roles as consultant, administrator, academic, and teacher-leader, illustrate and illuminate the potential of complexity leadership for the education system. They explore this potential as embedded in the context of an action research project enacted across all levels of the education system. These leadership practices may motivate and encourage formal and informal leaders to consider purposeful, planned ways to enable transformative change within complex adaptive systems.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.003

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 head0.334
GPT teacher head0.403
Teacher spread0.068 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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