Dialoguing with Body: A Self Study in Relational Pedagogy through Embodiment and the Therapeutic Relationship
Bibliographic record
Abstract
This article emerges from a self-study (Baird, 2004; Bergum, 2003; Grumet, 1990; Ham & Kane, 2004; Kitchen, 2005a, 2005b; Loughran, 2004) conducted as a requirement for a doctoral class at the University of Ottawa in the Faculty of Education. In this study, I reflected on my embodied experiences and the role of the body in my consulting practice in sport and performance psychology with athletes and dancers. Inspired by the work of Chehayl (2006), I engaged in a narrative analysis (Sands, 2002; Sparkes, 2002) of my own emerging autobiographic tale, and actively worked towards re-storying my body through a multi voiced dialogue between various "bodies" at play, both mine and those I interacted with. In light of my own personal experiences, combined with my growing understanding of the philosophy of the flesh (Lakoff & Johnson, 1999) and notions of embodiment in the therapeutic relationship, this study aimed to examine a) how I experienced my body in different domains of daily practice, b) what meaning I derived from these embodied experiences, c) what tensions, congruencies, and divergences existed within my embodied experiences, and d) what implications emerged relating to my consulting practice. Emerging from this self-study is the importance of learning to trust feel, learning to let go, and learning that I/matter. An embodied perspective appears to be an important part of a relational pedagogy and has the potential to facilitate healthy therapeutic relationships when integrated into a reflective, consulting, educational practice.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".