Self-Transformations of Health Professionals in the Field
Bibliographic record
Abstract
Health does not arise from health care. Perhaps we are facing an impasse and should we reconsider and reconceptualize the mandate of the health system. In order to improve our influence on the culture that often prevails in our institutions as well as the health of those institutions. This article examines the changes to the mandate of the health system seen in the light of self-transformations. This vision is based on a model that illustrates the transformations experienced by physicians following a mind-body training, i.e. Awakening the Sensible Being (ASB). The model shows the transformation process reported by physicians, after experiencing self-awareness of what they are doing, through experiencing the ASB, while developing a closer relationship with themselves. As it turned out, the training was beneficial for their health. Their expanded sense of self-awareness and quality of “savoir-être” brought on by the training contributes to their impression of “feeling whole” and provides them with a quality of presence that influences the type of care they can provide to their patients by considering the individual as a whole. This point of view could bring about a shift in the mandate of the health system and improve the health of caregivers and care-receivers as well, while contributing to widen the concept of health.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".