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Record W7155751586

A Study of Female Superintendents who Administer Public School Districts in British Columbia

2022· dissertation· en· W7155751586 on OpenAlexaboutno aff
Shannon Valerie Behan

Bibliographic record

VenueKU ScholarWorks (The University of Kansas) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipQualitative researchWork (physics)ResidenceCareer developmentSalaryGatekeepingCareer PathwaysEducational attainment
DOInot available

Abstract

fetched live from OpenAlex

Information available through the British Columbia School Superintendents Association shows that female superintendents in Western Canada are underrepresented compared to their male counterparts (https://bcssa.org/). This study examines the pathways current female superintendents took to obtain the role and explores their experiences on the job in an attempt to understand the reasons behind this gender disparity. Eight female superintendents serving in the province of British Columbia in the 2021–2022 school year were asked to describe the challenges, barriers, and opportunities for success that they encountered in their role as superintendent for this interpretive qualitative study. Qualitative analysis provided insight into how current female superintendents navigated their career paths, as well as recommendations for how to advance career opportunities for future female administrators. This study found that the women who are able to reach the superintendency do so due to access to strong and consistent mentorship opportunities, supportive partners and access to childcare or the decision to not have children, and residence in rural or suburban districts rather than urban ones. However, despite obtaining this top position, the superintendents interviewed all expressed that they faced backlash and gatekeeping from others in the public education system and had to make personal sacrifices to maintain the role. This study concludes that much work needs to be done within public education to ensure that women who aspire to the superintendency are supported to do so via dismantling the current barriers and ensuring equal access and opportunity for all.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.252
Threshold uncertainty score0.507

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0240.007
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.072
GPT teacher head0.324
Teacher spread0.252 · 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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