Social paediatrics: creating organisational processes and practices to foster health care access for children ‘at risk’
Bibliographic record
Abstract
In recent years understanding and addressing child health inequities has become a priority for research and practice. In this paper we share research insights on an approach that shows promise for engaging across the spectrum of health services to foster access to services and supports for child development to reduce child health inequities. As pathways of influence on children’s health and development extend beyond the biomedical domain new approaches to practice are needed to foster health care access and to mobilise needed supports. The Social Paediatrics Initiative has been introduced in one of Canada’s poorest inner city neighbourhoods where a disproportionate number of children experience adverse childhood events and enter school developmentally delayed. The research was undertaken in partnership with practitioners, community based organisations and the formal health services sector. The study gathered data from parents, community members and clinicians to understand the range of conditions that interfere with access to health care and to illustrate the ways the Social Paediatrics Initiative sought to foster access and provide care that was responsive to the health and developmental needs of children at risk because of their social and material circumstances. In particular we illustrate ways in which intersectoral and interdisciplinary partnerships enabled clinicians to provide needed supports to address the social determinants of health.
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.
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 | 0.061 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.032 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".