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Record W7133009292

Sex Education as Neoliberal Inclusion: Hetero-cis-ableism in Ontario' s 2015 Health and Physical Education Curriculum

2017· dissertation· W7133009292 on OpenAlexaboutno aff
TL McMinn

Bibliographic record

VenueTSpace · 2017
Typedissertation
Language
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumNeoliberalism (international relations)Physical educationInstitutionQueerSocial justiceEconomic JusticeKnowledge production
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, I investigate how hetero-cis-ableism and neoliberalism are tied to the production of “good” LGBT2SQ and disabled people and the expulsion of “bad” queers and crips within Ontario’s 2015 Health and Physical Education Curriculum. I argue that the move towards explicit or social justice education and the implementation of LGBT2SQ dialogue is not (simply) a way to represent equality, but a way of insuring the production of a specific type of person. Analysing the curriculum through Foucauldian and poststructuralist discourse analysis, I examined how the new content is being used to illicit hetero and cis-normative identities onto those that have otherwise been see as “less desirable.” Through a pedagogical mix of Queer and Crip Theory, this paper points to inconsistencies and flaws that are inherent within curriculum design itself, and how, regardless of intent, anything created for or within a neoliberal institution can never be fully inclusive.

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)0.006
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 score0.206
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.039
Scholarly communication0.0070.003
Open science0.0010.008
Research integrity0.0010.003
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 head0.078
GPT teacher head0.546
Teacher spread0.468 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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