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Record W2797576539 · doi:10.1123/apaq.2017-0106

Critical Pedagogy and APA: A Resonant (and Timely) Interdisciplinary Blend

2018· article· en· W2797576539 on OpenAlexaff
Maureen Connolly, William J. Harvey

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsMcGill UniversityBrock University
Fundersnot available
KeywordsEmbodied cognitionOppressionCritical pedagogyPedagogyInclusion (mineral)Variety (cybernetics)Relevance (law)SociologySocial justiceEngineering ethicsMental healthWork (physics)PsychologyEpistemologySocial sciencePolitical sciencePoliticsPsychotherapistComputer scienceEngineering

Abstract

fetched live from OpenAlex

Critical pedagogy owes much of its emergence, development, and ongoing relevance to the work of Paulo Freire whose legacy remains relevant for a next generation of scholars who seek to explore issues of inclusion, oppression, social justice, and authentic expression. An interdisciplinary dialogue between critical pedagogy and adapted physical activity is timely, appropriate, and should focus on complex profiles of neurodiversity, mental illness, and mental health, with emphasis on pedagogic practices of practitioners in service delivery and teacher educators who prepare them for professional practice. A case-based scenario approach is used to present practitioner and teacher educator practices. Concrete examples are provided for analyzing and understanding deeper issues and challenges related to neurodiversity in a variety of embodied dimensions in educational and activity contexts. We work with Szostak's approach to interdisciplinary research and model an analysis strategy that integrates and applies the methodological features of interdisciplinarity, adapted physical activity, and critical pedagogy.

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)0.030
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0110.076
Scholarly communication0.0220.024
Open science0.0030.018
Research integrity0.0060.017
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 head0.023
GPT teacher head0.410
Teacher spread0.387 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations45
Published2018
Admission routes1
Has abstractyes

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Same venueAdapted Physical Activity QuarterlySame topicInclusion and Disability in Education and SportFrench-language works237,207