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Record W2026519732 · doi:10.1080/01411920701434011

Sacrificial girls: a case study of the impact of streaming and setting on gender reform

2007· article· en· W2026519732 on OpenAlexaff
Emma Charlton, Martin Mills, Wayne Martino, Lori Beckett

Bibliographic record

VenueBritish Educational Research Journal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsDisadvantagedEquity (law)InequalityConstitutionAffirmative actionSociologyPolitical sciencePublic relationsGender studiesLaw

Abstract

fetched live from OpenAlex

This article reports on research funded by the Australian Research Council to investigate school responses to gender equity. It addresses the efforts of a disadvantaged school to tackle what they perceived to be gender inequalities, but in the process of constructing a top‐set and bottom‐set/stream class they are developing new forms of old inequalities and new forms of inequalities. This research indicates that despite popular assertions that girls' education has become the priority of schools and education systems, girls are being further disadvantaged through attempts to implement market strategies coupled with gender reform agendas grounded in liberal notions of equity and relying on unsophisticated notions of affirmative action. In addition, this study highlights the extent to which a media‐driven debate about boys' education has influenced the constitution of boys as the ‘new disadvantaged’ with the capacity to determine the nature of gender reform agendas and programmes in 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)0.005
metaresearch head score (Gemma)0.008
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 score0.028
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0280.011
Scholarly communication0.0050.003
Open science0.0020.009
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0090.001

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 head0.161
GPT teacher head0.494
Teacher spread0.333 · 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

Citations31
Published2007
Admission routes1
Has abstractyes

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