Researching lived experience in health professional education
Bibliographic record
Abstract
INTRODUCTION: Qualitative approaches have flourished in medical education research. Many research articles use the term 'lived experience' to describe the purpose of their study, yet we have noticed contradictory uses and misrepresentations of this term. In this conceptual paper, we consider three sources of these contradictions and misrepresentations: (1) the conflation of perspectives with experiences; (2) the conflation of experience with lived experience; and (3) the conflation of researching lived experience with phenomenology. We offer suggestions to facilitate more precise use of terminology. ARGUMENT: Our starting point is to free researchers from unnecessary shackles: Not every problem in medical education should be studied through experience, nor should every study of experience be phenomenological. Data based on participants' perceptions, beliefs, opinions and thoughts, while based on reflections of experiences, are not in and of themselves accounts of experience. Lived experiences are situated, primal and pre-reflective; perspectives are more abstract. Lived experience-as opposed to experiences as such-deeply attune to bodies, relationality, space and time. There is also a difference between experiences as lived, how a person makes sense of these and what the researcher interprets and represents. Phenomenology is a meaningful approach to the study of lived experience, but other approaches, such as narrative inquiry and self-study, can also offer useful avenues for undertaking this type of research. DISCUSSION: We aim to broaden researchers' scope with this paper and equip researchers with the information they need to be clear about the meaning and use of the terms experience and lived experience. We also hope to open new methodological possibilities for researching experiences as lived and, through highlighting tensions, to prompt researchers of lived experience to strive for ontological closeness and resonance.
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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 | 0.041 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".