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Record W4403114536 · doi:10.1080/13573322.2024.2408561

A figurational analysis of Health and/or Physical Education teacher educators’ conceptualisations of policy, and their sociogenesis

2024· article· en· W4403114536 on OpenAlexaff
Laura Alfrey, Dylan Scanlon, David Aldous, Jenna R. Lorusso, Kellie Baker, Christopher Clark, Mo Jafar

Bibliographic record

VenueSport Education and Society · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhysical educationPedagogySociologyTeacher educationPsychology

Abstract

fetched live from OpenAlex

Policy engagement is key to promoting ‘quality’ physical education yet it has been identified as a ‘grand challenge’ for Health and/or Physical Education (H/PE) internationally. All H/PE professionals, including teacher educators, have a collective responsibility to engage with policy but existing research tells us little about how H/PE teacher educators (H/PETEs) understand and engage with policy. It is important to examine H/PETEs conceptualisations of policy for a few reasons, not least because teacher educators play a crucial role in supporting future generations of teachers who themselves will need to engage with policy as a core feature of their professional lives. Drawing on figurational sociology, and the concept of assemblage, this paper offers insights into the nature and development – or sociogenesis – of teacher educators’ conceptualisations of policy. The data shared in this paper was generated through semi-structured interviews with 12 H/PETE from 7 countries. Inductive-deductive analysis – drawing largely on figurational concepts such as interdependence, power, habitus and sociogenesis – revealed that H/PETEs conceptualised policy as: (i) informing intended action and change; (ii) a way to govern practice; (iii) imposition and possibility. In terms of how these conceptualisations came to be, key features of the H/PETE figuration that were identified as influential include: (i) interdependence with human and non-human elements; (ii) balances of power and (iii) social and individual habitus. It is concluded that capitalising on these elements through professional learning, for example, could support H/PETEs in engaging with policy in productive and meaningful ways. Given that engaging with policy is viewed as a collective responsibility of H/PETEs, and many – if not all – of the H/PETEs felt they needed support in this regard, this should be a key focus for the field.

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)0.019
metaresearch head score (Gemma)0.018
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 score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0070.034
Scholarly communication0.0100.011
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.075
GPT teacher head0.491
Teacher spread0.416 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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