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Record W4398249054 · doi:10.7202/1111524ar

An Examination of Educational Leadership Preparation in Ontario: Are Principals Prepared to Lead Equitably?

2024· article· en· W4398249054 on OpenAlexaffvenueabout
Nia Spooner

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLead (geology)Business

Abstract

fetched live from OpenAlex

In response to the changing demographics of schools in Canada and efforts to better equip principals to challenging inequity, leadership preparation programs have adopted new policies focused more on leading with an equity lens. However, studies have demonstrated a disconnect between what is covered in these leadership programs and how school principals actually perceive their ability to lead equitably and work with diverse learners. Six current school principals and vice principals in Ontario, Canada who have successfully completed a Principal Qualification Program (PQP) course were interviewed to understand their perceptions on the program’s ability to prepare them to lead, and their perceptions on concepts of equity, diversity, and inclusion (EDI). The racial experiences and identities of each participant shaped their definitions of EDI, as well as their understandings of difference. Study findings indicate several critical areas of change for principal preparation programs in Ontario: training guidelines, efforts to prepare educators to be equitable leaders, and the educators’ perceptions on their preparedness to lead. Utilization of Critical Race Theory in Education and Applied Critical Leadership additionally help frame analysis and support the need to integrate culturally relevant pedagogical practice into leadership preparation programs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.182
GPT teacher head0.439
Teacher spread0.256 · 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 designObservational
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

Citations1
Published2024
Admission routes3
Has abstractyes

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