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Record W202841197 · doi:10.4324/9780203807170

Research Methods in Physical Education and Youth Sport

2012· book· en· W202841197 on OpenAlexaboutno aff
Kathleen Armour

Bibliographic record

Venuenot available
Typebook
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical educationPsychologyPolitical scienceSociologyMathematics education

Abstract

fetched live from OpenAlex

Section 1 - Planning the research process 1. What is your research question - and why? - Kathleen Armour, University of Birmingham, UK, and Doune Macdonald, University of Queensland, Australia 2. Research principles and practices: paving the research journey - Doune Macdonald and Louise McCuaig, University of Queensland, Australia 3. Positioning yourself as a researcher: four dimensions for self-reflection - Juan-Miguel Fernandez-Balboa, Universidad Autonoma de Madrid, Spain, and Nathan Brubaker, James Madison University, USA 4. What counts as 'good' research? - Stephen Silverman, Teachers College, Columbia University, USA, and Eve Bernstein, Queens College, City University of New York, USA Section 2 - Methodology: the thinking behind the methods 5. Thinking about research frameworks - Richard Tinning, University of Queensland, Australia, and Katie Fitzpatrick, University of Auckland, New Zealand 6. Conducting ethical research - Jan Wright and Gabrielle O'Flynn, University of Wollongong, Australia 7. Qualitative approaches - Peter Hastie, Auburn University, USA, and Peter Hay, University of Queensland, Australia 8. Quantitative approaches - Beverley Hale and Dudley Graham, University of Chichester, UK 9. Are mixed methods the natural approach to research? - Stephen Gorard and Kyriaki Makopoulou, University of Birmingham, UK 10. Listening to young people's voices in physical education and youth sport research - Mary O'Sullivan and Eimear Enright, University of Limerick, Ireland Section 3 - Selecting the most appropriate method(s) 11. Reviewing literature - Thomas J. Templin, Purdue University, USA, and Gemma Pearce, University of Birmingham, UK 12. Experimental research methods in physical education and sports - Leen Haerens and Isabel Tallir, University of Ghent, Belgium 13. Measurement of physical activity - Stewart G. Trost and Kelly Rice, Oregon State University, USA 14. Surveys - Hans Peter Brandl-Bredenbeck and Astrid Kampfe, University of Paderborn, Germany 15. Observational studies - Marie Ohman and Mikael Quennerstedt, Orebro University, Sweden 16. Case study research - Kathleen Armour and Mark Griffiths, University of Birmingham, UK 17. Interviews and focus groups - Catherine D. Ennis, University of North Carolina, Greensboro, USA, and Senlin Chen, Iowa State University, USA 18. Narrative research methods: where the art of storytelling meets the science of research Kathleen Armour, University of Birmingham, UK, and Hsin-heng Chen, Loughborough University, UK 19. Action research in physical education: cycles, not circles! - Anthony Rossi and Wah Kiat Tan, University of Queensland, Australia 20. Visual methods in coaching research: capturing everyday lives - Robyn Jones and Sofia Santos, University of Wales Institute, Cardiff, UK Isabel Mesquita, Faculdade de Desporto, Porto, Portugal and David Gilbourne, University of Wales Institute, Cardiff, UK 21. Grounded theory - Nicholas L. Holt and Camilla J. Knight, University of Alberta, Edmonton, Canada, and Katherine A. Tamminen, University of British Columbia, Vancouver, Canada 22. Discourse analysis and the beginner researcher - Kathy Hall and Fiona C. Chambers, University College, Cork, Ireland Section 4 - Data analysis - consider it early! 23. Analysing qualitative data - Peter Hastie and Olga Glotova, Auburn University, USA 24. Analysing quantitative data - Beverley Hale and Alison Wakefield, University of Chichester, UK Section 5 - Communicating your research 25. Effective research writing - David Kirk and Ashley Casey, University of Bedfordshire, UK 26. The dissertation - Lisette Burrows, Fiona McLachlan and Lucy Spowart, University of Otago, New Zealand

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)0.132
metaresearch head score (Gemma)0.158
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.132
Threshold uncertainty score0.700

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.158
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0070.010
Science and technology studies0.0030.014
Scholarly communication0.0130.008
Open science0.0030.009
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0350.015

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 head0.484
GPT teacher head0.708
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations160
Published2012
Admission routes1
Has abstractyes

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