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Record W2156273207 · doi:10.46743/2160-3715/2013.1506

Single - sex Education in Northern Canada: A Case Study of Trapline Elementary School

2015· article· en· W2156273207 on OpenAlexaffabout
Simon Blakesley

Bibliographic record

VenueThe Qualitative Report · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSingle sexCLARITYQualitative researchPsychologyPedagogySociologyMathematics educationSocial science

Abstract

fetched live from OpenAlex

In this article I present findings from a 2012 case study of a northern Canadian public school organizing its classes in a single - sex configuration. Trapline School 1 , a Kindergarten to Grade 7 (K - 7) school in the, Yukon Territory, Canada, began organizing classes employing a single - sex configuration in 2007. The purpose of this research was to gain insights into the current status of single - gender education at Trapline School based on the perspectives of a range of stakeholders. This study specifically identifies and presents the perspectives of teachers, students, former students, School Council (comprised of parents), and school administration. Emerging from the analysis are a number of findings, including the perceived benefits and strengths of a single - sex approach to schooling and areas requiring further consideration or improvement. The study identifies the need for greater clarity regarding what is expected to be accomplished by the implementation of single - sex classes.

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)0.003
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 score0.076
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0430.006
Scholarly communication0.0040.001
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.177
GPT teacher head0.482
Teacher spread0.305 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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