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Teaching in Uncharted Waters: Seeking Critical Body Literacy Scripts

2012· article· en· W110877805 on OpenAlexaffvenueabout
Lorayne Robertson, Dianne Thomson

Bibliographic record

VenueAlberta Journal of Educational Research · 2012
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPsychologyScripting languageFraming (construction)Mathematics educationMedical educationLiteracyPedagogySchool teachersMedicineGeography

Abstract

fetched live from OpenAlex

Schools are places of learning, but they are also sites of struggle when fitness, obesity, and body image issues converge for students and teachers. Responding to teachers’ concerns about their students on diets, a Canadian teachers’ organization produced a body image program which included a training day for schools undertaking whole-school implementation. The teachers’ organization commissioned research to determine program outcomes. The research team interviewed 48 participating teachers. Data include: teacher responses to a post-training survey, interview transcripts, and artefacts from school visits. Findings indicate that implementation is impacted by resources and the complex ways that students’ and teachers’ bodies are positioned socially. While the program intent was to provide teachers with body image lessons, findings suggest that other supports are needed such as knowledge mobilization of body image research, critical framing to respond to issues, and a theoretical map such as critical body literacy in order to navigate these uncharted waters.

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)0.027
metaresearch head score (Gemma)0.053
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 score0.997
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0120.045
Scholarly communication0.0170.021
Open science0.0030.016
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.090
GPT teacher head0.484
Teacher spread0.394 · 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

Citations3
Published2012
Admission routes3
Has abstractyes

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