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
This guide identifies specific self-management support interventions which have demonstrated reach and impact, and identifies the factors that activate patients, clinicians and the healthcare system to engage with these interventions.The interventions presented in this guide reflect learning from working with approximately 9,000 patients in the Manaaki Hauora – Supporting Wellness campaign.The Manaaki Hauora – Supporting Wellness campaign:Counties Manukau has over 67,000 people with long-term conditions. More than half of these have diabetes, and more than quarter have two or more co-existing conditions.The Manaaki Hauora – Supporting Wellness campaign led by Ko Awatea, the centre for healthcare improvement and innovation at Counties Manukau Health, aimed to provide self-management support for people living with long-term conditions in Counties Manukau.The campaign covered 16 collaborative teams working in different settings and clinical contexts. Each team had a unique aim which contributed to the overall campaign aim. Ten of the teams, whose projects best illustrate the interventions with the greatest reach and impact, are featured in this guide.<br>
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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