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Record W2027406940 · doi:10.1080/01425692.2013.836056

Playing it down/playing it up: girls’ strategic negotiations of academic success

2013· article· en· W2027406940 on OpenAlexaffabout
Rebecca Raby, Shauna Pomerantz

Bibliographic record

VenueBritish Journal of Sociology of Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsBrock University
Fundersnot available
KeywordsNegotiationAgency (philosophy)NarrativeSociologyAcademic achievementPublic relationsPedagogyGender studiesPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Through the lens of post-structural agency, this article focuses on how self-identified smart girls strategically negotiate their academic identities within the gendered terrain of the school. Based on interviews with 51 smart high school girls in Canada, our analysis complicates current narrative of girls’ easy achievement in school. Participants discussed balancing the hazards of being overly academic with the rewards of academic success. In response to this tension, girls carefully and consciously performed ‘smart girlhood’, drawing on resources that are more available to some girls than others, and indicating that girls’ academic success is neither easily embraced nor unambivalently accepted.

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)0.005
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 score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.021
Scholarly communication0.0110.003
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.054
GPT teacher head0.367
Teacher spread0.313 · 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

Citations19
Published2013
Admission routes2
Has abstractyes

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