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Record W2964250751 · doi:10.35608/ruraled.v40i2.777

“I’m Not Where I Want to Be”: Teaching Principals’ Instructional Leadership Practices

2019· article· en· W2964250751 on OpenAlexaffabout
Dawn Wallin, Paul Newton, Mickey Jutras, Jordan Adilman

Bibliographic record

VenueThe Rural Educator · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsSaskatoon City HospitalUniversity of Saskatchewan
Fundersnot available
KeywordsInstructional leadershipROWEPrincipal (computer security)Educational leadershipTeacher leadershipPedagogyPsychologyLeadershipLeadership styleSociologyMathematics educationManagementSocial psychology

Abstract

fetched live from OpenAlex

This paper reports on the ways in which teaching principals in rural schools in Alberta, Manitoba, and Saskatchewan, Canada enact instructional leadership within the five leadership domains conceptualized by Robinson, Lloyd, and Rowe (2008). Although participants suggested that they were “not where they wanted to be” in their efforts to enact instructional leadership, their actions demonstrate exemplary practice in this regard. The nature of the discourse perpetuated by leadership groups and teachers’ associations that equates instructional leadership with classroom visits only has the effect of decreasing teaching principals’ self-efficacy as instructional leaders. We argue for recognition of these leaders’ efforts to support learning, and a reconstitution of the role of the teaching principal such that instructional leadership expectations are realistically manageable for leaders in small rural schools.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.139
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.006
Scholarly communication0.0040.001
Open science0.0010.002
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 head0.259
GPT teacher head0.433
Teacher spread0.173 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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