Dilemmas in embodied methods: Towards holistic description in qualitative research
Bibliographic record
Abstract
Our bodily experience is a recognised conduit to understanding our social world and those who dwell within it. Concurrently, embodied research emerged as a legitimate and thought-provoking methodological approach that goes further to access depth in understanding than more distanced approaches. Yet such methods imply a closeness with the participants and context that raises some philosophical and ethical dilemmas. This paper aims to engage with these debates using examples from the author's experiences conducting embodied research in various global locales in the broad field of sport and physical culture. A conceptual model is built and employed in these discussions, and in doing so, the concept of ‘holistic description’ is developed to highlight the potential of embodied methodologies to engender further trust between the researcher, the reader and participants. It is hoped these developments will embolden researchers thinking about embodied research with further confidence and knowledge to pursue such involved and empathetic routes to knowing while staying true to the fundamental principles of qualitative enquiry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.423 | 0.307 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.014 | 0.122 |
| Scholarly communication | 0.035 | 0.033 |
| Open science | 0.008 | 0.030 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".