Social care innovation by the social economy in Manchester, Greater Manchester and the North of England: preparatory material for webinar
Bibliographic record
Abstract
This paper sets out four case studies of social economy social care models, approaches and/oractivities, primarily within Manchester and Greater Manchester - PossAbilities (Page 10); Be Caring (P. 14); North West Care Co-operative (NWCC) (P. 19); and HMR Circle (P. 22).These examples illustrate some responses to the ‘crisis of social care’ within the UK, whether bythose delivering contracted public services, complementary services, and/or attempting a moreprofound system change in how social care is understood and delivered. They follow a discussion ofthe context for innovation within social care in the UK and Greater Manchester, and the related trends and developments that this has given rise to (including some shorter case studies ofinteresting models). This report also formed the basis for a learning exchange webinar between the City of Manchester and Ville de Montréal on 1st October 2019.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".