The music of trees: the intergenerative tie between primary care and public health
Bibliographic record
Abstract
Stories help us frame and understand complex ideas and challenges. Metaphors are particularly powerful linguistic devices that guide and extend our thinking by bridging conceptual domains, for example to consider the brain as a digital computer. Trees are widely used as metaphors for broad concepts like evolution, history, society, and even life itself, i.e. 'the tree of life'. Tree-like diagrams of roots and branches are used to demonstrate historical and cultural relationships, for example, between different species or different languages. In this paper, we describe a theatrical character called a tree doctor which is a living metaphor. A human being, namely the author, lectures, acts or dances as a tree and offers lessons to Homo Sapiens about 'holistic' ideas of health. The character teaches us to not only see the value of our relationships to trees, but the importance of seeing forests as well the individual trees. The metaphorical statement that we should not 'miss the forest for the trees' means we should learn to think of health embedded in systems and communities. In medicine, we too often focus on individual molecules, pharmaceuticals, or even patients and miss the bigger picture of public and environmental health. In a time of great ecological system change, the tree doctor points to broad ethical responsibility for each other and future generations of humans and other living creatures. The character embraces arts and particularly music as a powerful way of infusing purpose and improving the qualities of our lives together, especially as we age. The tree doctor knows the value of intergenerational relationships. But it also points to intergenerative innovations across many cultural domains, disciplines and professions. The tree doctor supports primary care and empowers the value of intergenerational relationships, art and music in the recommendations doctors make to patients to improve their health and well-being.
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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 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".