Crafting a praxis-oriented culture concept in the health disciplines: conundrums and possibilities
Bibliographic record
Abstract
'Culture' is a key concept in the social sciences. It also figures prominently in health science discourses. Yet, it is an imprecise and politically charged term. Due to a variety of factors, health care professionals may tend to use notions of culture that can be easily applied. Dangers are posed when using simplified culture concepts, however, because they act as 'interpretive lenses' - lenses that may generate cultural stereotypes, lead health professionals to miss key interactions and processes in the provision of care, and simplify the cultural complexities surrounding the position(s) of both the health care providers and their clients. Two cases of eldercare are analysed to demonstrate the multi-layered intricacies of the concept of culture. The overall point is that 'culture' is a highly complex and dynamic term; the way in which it is conceptualized and used has enormous consequences for health care.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.026 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".