Opinion: the longevity of social prescribing around the world is contingent on student involvement
Bibliographic record
Abstract
Purpose Social prescribing is a growing movement in healthcare systems worldwide. This article shares the opinion of the authors that social prescribing’s longevity is dependent on student involvement. Design/methodology/approach To argue this viewpoint, the authors share examples of how student collaborations have previously been utilised successfully to promote social prescribing. Findings It is concluded that future social prescribing success could therefore rely on continued student involvement. Research limitations/implications This work is a viewpoint article, meaning it is subjective in nature and influenced by the authors’ lived previous experiences of the benefits they noticed to their learning by themselves being involved with social prescribing schemes as students. Originality/value This original viewpoint article offers a valuable perspective regarding what education may be necessary in relation to social prescribing. This is because it shares the viewpoints of authors who all have different lived experiences of social prescribing education by holding various roles within worldwide social prescribing peer-learning schemes.
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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 | 0.017 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".