Compassionate care? A critical discourse analysis of accreditation standards
Bibliographic record
Abstract
CONTEXT: We rely upon formal accreditation and curricular standards to articulate the priorities of professional training. The language used in standards affords value to certain constructs and makes others less apparent. Leveraging standards can be a useful way for educators to incorporate certain elements into training. This research was designed to look for ways to embed the teaching and practice of compassionate care into Canadian family medicine residency training. METHODS: We conducted a Foucauldian critical discourse analysis of compassionate care in recent formal family medicine residency training documents. Critical discourse analysis is premised on the notion that language is connected to practices and to what is accorded value and power. We assembled an archive of texts and examined them to analyse how compassionate care is constructed, how notions of compassionate care relate to other key ideas in the texts, and the implications of these framings. RESULTS: There were very few words, metaphors or statements that related to concepts of compassionate care in our archive. Even potential proxies, notably the doctor-patient relationship and patient-centred care, were not primarily depicted in ways that linked them to ideas of compassion or caring. There was a reduction in language related to compassionate care in the 2013 standards compared with the standards published in 2006. CONCLUSIONS: Our research revealed negative findings and a relative absence of the construct of compassionate care in our archival documents. This work demonstrates how a shift in curricular focus can have the unintended consequence of making values that are taken for granted less visible. Given that standards shape training, we must pay attention not only to what we include, but also to what we leave out of formal documents. We risk losing important professional values from training programmes if they are not explicitly highlighted in our standards.
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How this classification was reachedexpand
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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".