Contextualizing Leisure Research to Encompass Complexity in Lived Leisure Experience: The Need for Creative Analytic Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Many qualitative manuscripts published on the phenomenon of leisure remain post positivist privileging the traditional scientific method as the way of conducting and representing research. Such traditional approaches to research lead to debates about whether interpretative accounts can accurately, adequately, directly, or completely capture, depict, describe, or portray social life. In response to this crisis of representation, many leisure scholars have adopted creative analytic practice (CAP), which allows for the creation of imaginative and creative representation including autoethnography, fiction stories, visual images, poetry, experimental media, and performance. CAP reflects a deliberate attempt to demonstrate that the processes and products of qualitative inquiry are inextricably linked. CAP purposefully engages issues connected to subjectivity, authority, authorship, reflexivity, and representational form. Keywords: crisis of representationcrisis of legitimationqualitative researchinterpretation Acknowledgements We are grateful to those individuals who submitted papers for consideration in this special issue and encourage those scholars to continue to endeavor using Creative Analytic Practice. A special debt of gratitude is owed to Bill Stewart who provided initial insight and feedback as we drafted this piece. We also appreciate the energy, enthusiasm, dedication and thoughtful comments of those reviewers who provided their expertise both topically and methodologically to this undertaking: Stacey Altman, East Carolina University; Lisbeth Berbary, University of Georgia; Roy Cain, McMaster University; Dan Cook, University of Illinois; Lynn Cory, Clemson University; Jim Denison, University of Bath; Greg Dimitriadis, University of Buffalo; Sherry Dupuis, University of Waterloo; Dan Dustin, University of Utah: Myron Floyd, North Carolina State University; Heather Gibson, University of Florida; Ann Marie Guilmette, Brock University; Jodi Kaufmann, Georgia State University; Beth Kivel, California State University, Sacramento; Sharon Knight, East Carolina University; Jamie Lewis, University of Georgia; Pirkko Markula, University of Bath; Blaise Astra Parker, University of Georgia; Michael Roth, University of Vermont; Leslie Rush, University of Wyoming; Diane Samdahl, University of Georgia; Mike Silk, University of Maryland; Erin Sharpe, Brock University; Bob Stebbins, University of Calgary; Bill Stewart, University of Illinois; Joe Tacchi, Queensland University of Technology; Brent Wolfe, University of Southern Mississippi; Careen Yarnal, Penn State University; Matt Zuefle, The University of Mississippi
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it