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Record W1984805386 · doi:10.1080/09518398.2011.561817

Picturing oppression: seventh graders’ photo essays on racism, classism, and sexism

2011· article· en· W1984805386 on OpenAlexaffabout
Özlem Sensoy

Bibliographic record

VenueInternational Journal of Qualitative Studies in Education · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRacismSociologyMainstreamOppressionGender studiesSituatedCurriculumCritical pedagogyIntersectionalityIdentity (music)Critical theoryContext (archaeology)PedagogyMulticultural educationMulticulturalismPoliticsPolitical scienceAesthetics

Abstract

fetched live from OpenAlex

This study, situated in an inner‐city school in Western Canada, involved 20 seventh graders producing photo essays about living with racism, classism, or sexism. Two questions guided the study: (1) How do students working with a critical pedagogue conceptualize their own experiences with race, class, and gender in ways that either interrupt or reinscribe dominant mainstream curricular narratives?; and (2) To what extent can visual methods serve to open up and expand researchers’ understanding of students’ conceptions of their lived experiences in the context of a critical pedagogy classroom? This study drew upon critical pedagogy, critical multicultural education, and visual methodology. Issues of societal curriculum and identity were central to this work. Students’ photo essays not only revealed some patterns of mainstream discourses related to race, class, and gender, but also revealed some very sophisticated understandings of how social issues play out in institutional systems.

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)0.005
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 score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.357
GPT teacher head0.473
Teacher spread0.117 · 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

Citations28
Published2011
Admission routes2
Has abstractyes

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