Bibliographic record
Abstract
Whole Person Care aims to be deeply present to the person in the patient; acknowledging the integration of physical, psychosocial and spiritual facets of human experience, and creating a space in which healing, or a greater sense of wholeness, may occur. Music offers a potent tool in this endeavor. With its inherent capacity to engage body, mind and spirit, music can stimulate or calm, transport us to other times and places, reach our innermost emotions, and connect us to ourselves, our loved ones and our spirituality. In palliative care, music therapy joins with whole person care to meet patients and their loved ones as fully as possible.Concepts central to whole person care will be presented and illustrated through the lens of clinical music therapy. For example, exploring how the skilful use of music addresses many dimensions of personhood will highlight Cassell’s concept of personhood. Demonstrating the ability of a significant melody to access and externalize personal meaning will integrate ideas from Frankl on meaning. Observing how relationship and creativity function as healing connections will draw from Mount, as will the idea of helping one move on a continuum from suffering to healing (Mount, Hutchinson, Kearney). The role of the health care professional as a ‘vulnerable-enough’ caregiver (Papadatou) or ‘wounded healer’ (Kearney) will also be touched upon. Throughout the presentation, poignant images, stories and video clips of patients engaging in music therapy at the end of life will serve to both enliven the didactic material and demonstrate how music therapy can create a space in which experiences of greater integrity may occur.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".