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Record W4230748005 · doi:10.24124/2005/bpgub366

Single-gender classrooms: Improving achievement of grade 9 males.

2005· dissertation· en· W4230748005 on OpenAlexaffabout
Pamella Groves

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of Northern British ColumbiaUniversity of British ColumbiaLibrary and Archives Canada
Fundersnot available
KeywordsConversationPsychologyClass (philosophy)Single sexMathematics educationAcademic achievementDevelopmental psychologyQualitative researchStudent achievementPedagogySociology

Abstract

fetched live from OpenAlex

This qualitative research project examined the experience of participants in single gender Math and English classes within a coeducational middle school in British Columbia, Canada. Through interviews, 30 boys and 2 teachers described a typical day in single-gender and mixed-gender classes. Responses provided insight into the attitude, behavior and achievement of Grade 9 male students. Teaching strategies tailored to best meet the needs of male students were investigated. Students and teachers documented gains in achievement. The greatest improvement in achievement occurred with below average students; students with A-averages disliked the class. Conversation, comfort, support, participation, joking around, and physical interactions increase, yet bullying behaviors decrease. The boys\u2019 culture does not change; it is merely strengthened. Finally, classroom management with boundaries and lessons that reflect the boys\u2019 need for physical and verbal interactions leads to a classroom that serves the academic and social needs of the boys.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.358
Teacher spread0.275 · 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 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

Citations0
Published2005
Admission routes2
Has abstractyes

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