267 Bridging Health Equity: A Model for Primary Healthcare in the Hamilton, Ontario’s Keith Neighbourhood
Bibliographic record
Abstract
OBJECTIVES/GOALS: A primary care clinic is opening in the Eva Rothwell Center (ERC) located in the Keith Neighbourhood of Hamilton, Ontario. This new clinic aims to address rampant health disparities in the community. Effective delivery of health services requires a robust model of care that meets and sustains the specific needs of the community and clinic providers. METHODS/STUDY POPULATION: The primary objective of this study is to describe the current health needs of Keith Neighbourhood residents. The secondary objective is to describe the needs of health providers working within the ERC health clinic. Data collection will involve the collection of primary data (through methods such as surveys and interviews) and secondary data (including historical and current census data). Primary data analysis for primary will use conventional quantitative and qualitative methods. Finally, researchers will use the analyzed data to develop a context-appropriate initial model of care for the ERC health clinic and a subsequent evaluation plan to assess the model’s effectiveness and sustainability. RESULTS/ANTICIPATED RESULTS: All primary and secondary data will be synthesized into a report that will inform the development and implementation of two main deliverables. The first deliverable will be a framework for the clinic’s initial model of care that is context-appropriate to the current needs of the Keith Neighbourhood. The model of care will be culturally sensitive and trauma-informed. The second deliverable will be an evaluation plan for the clinic that can be used to continuously iterate on the initial model, ensuring its sustainability. Furthermore, the project’s process may be extrapolated into a framework that could be used to establish primary care clinics within other priority communities. DISCUSSION/SIGNIFICANCE: The proposed model of care will enable practitioners to deliver relevant and timely health services while being adaptable to the community’s evolving needs. It will help improve the Keith Neighbourhood residents' long-term health and social outcomes. This project will contribute to and inform the development of the field of translational science.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".