MétaCan
Menu
Back to cohort
Record W7098975835

Taught Bodies

2000· article· en· W7098975835 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicData Privacy and Cybersecurity
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Reading (process)StatueCurriculumWhite (mutation)Space (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

Taught Bodies proves a quick and tantalizing read about the discursive and material body in a variety pedagogical contexts. Consisting of a collection of papers delivered at a 1997 Australian conference, “Pedagogy and the Body, ” Taught Bodies offers an interdisciplinary romp through the school and university classroom, the art gallery, the theatre, popular crime fiction, the cinema, and of course, the boudoir, exposing and exploring the body present and produced in these contexts. With fourteen chapters and an introduction all in slightly over 200 pages, it is a quick and breezy text intended to arouse our interest—draw our gaze—to the often overlooked and taken-for-granted Journal of the Canadian Association for Curriculum Studies 262 fact that the body and pedagogy, “are inextricably entwined, ” as stated in the introduction. On this level it works. After experiencing this text, readers may indeed begin to see bodies in pedagogy everywhere. In my own case, after reading the text I was reminded about the body in teacher education: a space oddly enough not addressed in Taught Bodies but important nonetheless, wherein youthful, more often white and female student bodies train to be teacher bodies, and where, over greater time, graduate students bodies are turned in professorial bodies. Also I was suddenly made more aware of the statue of a male and female adult, naked but with fig leafs prominent, holding books aloft, that stands in the courtyard at the faculty of education where I teach. Among a host of other questions, the statues capture for me now the question of why and when teaching and taught bodies are rendered simultaneously visible and invisible; necessarily seen and not seen in relation to pedagogy, to literacy and to exalted texts, held, in this instance, away from and above the body.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.338
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0090.006
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.3380.186

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 head0.019
GPT teacher head0.306
Teacher spread0.288 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

Explore more

Same topicData Privacy and CybersecurityFrench-language works237,207