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Record W3043520410 · doi:10.7202/1070274ar

Breathing Life into Sexuality Education: Becoming Sexual Subjects

2020· article· en· W3043520410 on OpenAlexvenueno aff
Louisa Allen

Bibliographic record

VenuePhilosophical Inquiry in Education · 2020
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHuman sexualityMetaphorContext (archaeology)CurriculumTransformative learningSociologySexuality educationAestheticsPsychologyGender studiesPedagogySex educationPhilosophy

Abstract

fetched live from OpenAlex

This paper thinks with Todd’s (2017) ideas around ‘breathing life into education’ in relation to the curriculum area of sexuality education. It explores how this metaphor might be employed as a method for re-animating thought about the nature and purpose of sexuality education. The paper argues that sexuality education suffers from the stifling effects of instrumentalism and a neoliberal normativity that seeks to micro-manage the lives of students. Within sexuality education, this finds expression in a repetitive emphasis on reducing unplanned pregnancies and sexually transmissible infections. Confined by these foci, sexuality education’s pedagogical possibilities and transformative potential are limited. Breathing life into sexuality education offers opportunities for shaping this curriculum area as sensuous event. It also provides a life-enhancing pedagogical orientation that shifts focus from determining student’s imagined sexual futures, to attending to uncertainty in the present. Thinking with Todd’s ideas within the realm of sexuality education is an attempt to exercise their utility within a specific curriculum context. The paper also endeavours to press the metaphor of breath further, to characterise it as an act that is both mundane and profound. The implications of this conceptualisation for thinking about change in sexuality education are explored.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.159
GPT teacher head0.449
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designObservational
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

Citations7
Published2020
Admission routes1
Has abstractyes

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