1 Motivation, Justification, Normalization: Talk Strategies Used by Canadian Medical Tourists Regarding Their Choices to Go Abroad for Hip and Knee Surgeries
Bibliographic record
Abstract
Contributing to health geography scholarship on the topic, the objective of this paper is to reveal Canadian medical tourists ’ perspectives regarding their choices to seek knee replacement or hip replacement or resurfacing (KRHRR) at medical tourism facilities abroad rather than domestically. We address this objective by examining the ‘talk strategies ’ used by these patients in discussing their choices and the ways in which such talk is co-constructed by others. Fourteen interviews were conducted with Canadians aged 42-77 who had gone abroad for KRHRR. Three types of talk strategies emerged through thematic analysis of their narratives: motivation, justification, and normalization talk. Motivation talk referenced participants ’ desires to maintain or resume physical activity, employment, and participation in daily life. Justification talk emerged when participants described how limitations in the domestic system drove them abroad. Finally, being a medical tourist was talked about as being normal on several bases. Among other findings, the use of these three talk strategies in patients ’ narratives surrounding medical tourism for KRHRR offers new insight into the language-health-place interconnection. Specifically, they reveal the complex ways in which medical tourists use talk strategies to assert the soundness of their choice to shift the site of their own medical care on a global scale while also anticipating, if not even guarding against, criticism of what ultimately is their own patient mobility. These talk strategies provide valuable insight into why international patients are opting to engage in the spatially explicit practice of medical tourism and who and what are informing their choices. Keywords:
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".