Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social prescribing is an approach that aims to improve health and well-being. It connects individuals to non-clinical services and supports that address social needs, such as those related to loneliness, housing instability and mental health. At the person level, social prescribing can give individuals the knowledge, skills, motivation and confidence to manage their own health and well-being. At the society level, it can facilitate greater collaboration across health, social, and community sectors to promote integrated care and move beyond the traditional biomedical model of health. While the term social prescribing was first popularised in the UK, this practice has become more prevalent and widely publicised internationally over the last decade. This paper aims to illuminate the ways social prescribing has been conceptualised and implemented across 17 countries in Europe, Asia, Australia and North America. We draw from the 'Beyond the Building Blocks' framework to describe the essential inputs for adopting social prescribing into policy and practice, related to service delivery; social determinants and household production of health; workforce; leadership and governance; financing, community organisations and societal partnerships; health technology; and information, learning and accountability. Cross-cutting lessons can inform country and regional efforts to tailor social prescribing models to best support local needs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it