Is our incapacity for conversation a serious barrier to person centred medicine?
Bibliographic record
Abstract
In 2007, Vessey and Blauwkamp readdressed Gadamer’s 1972 essay ‘‘The Incapacity for Conversation’’ where the question of how changes in present society communicates is creating an incapacity for conversation. This manuscript further explores this idea about whether we are becoming influenced and charmed by the brevity of #communication i.e., text messaging, tweets, emoticons, speed-dating, and sound-bites. These popular cultural phenomena can become even more pronounced in medicine, where communication as conversation is reduced to checklists, interdisciplinary and patient debriefings, numeric technologic test results and perhaps a from of speed-patient(ing). Consequently, we may be eroding our already undervalued capacity to participate in person centred conversations due to the demands of modern medical 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 | 0.047 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.031 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".