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Record W4401499774 · doi:10.1080/15700763.2024.2390490

Principal Allyship in Saskatchewan Inner-City Schools

2024· article· en· W4401499774 on OpenAlexaffabout
Mickey Jutras, Dawn Wallin

Bibliographic record

VenueLeadership and Policy in Schools · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of SaskatchewanSt. Francis Xavier University
Fundersnot available
KeywordsPrincipal (computer security)Inner cityMathematics educationSociologyGeographyPublic administrationPedagogyPolitical sciencePsychologySocioeconomicsComputer science

Abstract

fetched live from OpenAlex

Schools that are described as “inner-city” schools in Saskatchewan are commonly found in communities plagued with racialized poverty that consist predominantly of Indigenous families. Principals who are considered to be allies by Indigenous communities work alongside Indigenous students, families, and staff to challenge the effects of colonization and marginalization, and collectively work on student learning outcomes. This article reports on the findings of a study that examined school-based leadership within an inner-city Saskatchewan school with a high Indigenous population. The purpose of the study was to invite Indigenous people associated with schools to discuss school leadership and the extent to which school-based leaders can work as allies to improve the experiences of Indigenous students. Participants identified significant challenges within inner-city schools rooted in colonization, racism, and poverty, as well as mitigating measures that school leaders can take to offset some effects of these challenges. The need for principals to be identifiable to the community through their actions was significant. This included demonstrating a commitment to listening and learning from the community; maintaining high expectations for students as well as staff; focusing on relationship building with all segments of the community; welcoming diverse perspectives in decision-making, and; challenging and changing unjust processes and 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)0.003
metaresearch head score (Gemma)0.002
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 score0.551
Threshold uncertainty score0.892

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0230.005
Scholarly communication0.0060.002
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.195
GPT teacher head0.427
Teacher spread0.232 · 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
Published2024
Admission routes2
Has abstractyes

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