Healing: Toward a practical definition and clinical understanding
Bibliographic record
Abstract
Healing is included as one of the fundamental goals of medicine. It is a term frequently used in health care but often poorly defined and misunderstood. The purpose of this workshop is to address this problem and will be interactive and discussion driven. We will briefly present a 'working definition' of the concept which will include an outline of the 'realms' of healing work from the diagnostic process through to management and treatment. We will use a case based introduction as a way of demonstrating our understanding of what the healing process entails. We will offer a number of alternate definitions of the term and examine the phenomenology of “lived experience” of illness using the work of Merleau-Ponty, Toombs, Cavel and Cassell and others. Existential issues which lead to the “brokenness” experienced through illness and suffering will be explored. We will open and facilitate a discussion of aspects and methods of healing with the goal being a clear and, to some degree, operationalised understanding of the concept(s) which we hope will be clinically useful and demonstrate the path(s) to “wholeness”. Areas which might be explored in the workshop will include the phenomenology of illness and suffering, the use of the clinician/patient/family relationship as the healing vehicle, intersubjectivity and empathy, the importance of narrative, collaborative and multidisciplinary care, the need to combine objective, empirical (evidence based) knowledge and subjective first person (experiential) knowledge to understand the lived experience of suffering and illness and the methodology of Person Centered and whole person care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.089 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.011 | 0.118 |
| Scholarly communication | 0.032 | 0.048 |
| Open science | 0.010 | 0.030 |
| Research integrity | 0.017 | 0.035 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".