Sláintecare action plan report Q1 deliverables
Bibliographic record
Abstract
A detailed Sláintecare Action plan for 2019 was completed and published on March 13th 2019. The Action Plan sets out detailed deliverables and timeframes for 239 deliverables that are to be progressed in 2019 as part of the implementation of the Sláintecare vision and firmly establishes a programmatic approach to the delivery of the Sláintecare Strategy. The 28 deliverables for Quarter 1 are on track. \nIn the first quarter of this year the Sláintecare Programme Implementation Office (SPIO) team has been mobilised to support and drive the implementation of these projects working in partnership with the Department units, the HSE and other partners. \nDuring the first quarter of 2019, the Sláintecare Executive Director and SPIO team have continued to engage with citizens, stakeholders and frontline staff across the health and social care service to ensure that these voices are involved in the design and delivery of the Sláintecare vision. A number of workshops, site visits and engagement events have taken place around the country with frontline clinicians. Two briefing sessions have been held with members of both the Joint Committee on Health and the former Committee on the Future of Healthcare. The Citizen Engagement and Empowerment Programme continues to be rolled out, with two regional events taking place in Quarter 1. \nThe SPIO team continuously engage with the HSE Leadership Team and Strategic Transformation Office to enable an integrated and cohesive approach to the implementation of the Sláintecare 2019 deliverables aligned with the National Service Plan.
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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 | 0.024 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.406 | 0.207 |
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".