Exploring income security offered through primary care: a mixed-methods process evaluation
Bibliographic record
Abstract
The objective of this study was to understand the components of a novel income security program offered through an inner-city primary health care team in Winnipeg, Manitoba. Through process evaluation, key patient characteristics and program components were considered, in accordance with the goals of a program-stakeholder evaluation committee. Both quantitative and qualitative data were collected via chart review, document summary, and interviews with both the program provider and multiple program participants. Mixed methods were incorporated into both data collection and data analysis to reflect key program processes and activities. The process evaluation revealed that the Income Security Health Promoter (ISHP) program, with one full-time service provider, provided comprehensive income security support services to 415 clients within its first 20 months of operation. Clients engaged in the program were medically complex, and received key services in the domains of income security supports (73.3%), associated service assistance (61.7%) (a category that includes housing, medication, food, and transportation), budgeting supports (50.0%), and referrals to other services (45.0%). Making contact and establishing relationships with clients was a prevalent feature of program activity (95%). The process evaluation was able to ascertain that the ISHP program operated consistently with the stated goals, and did so in a way that provided meaningful enrichment in the lives of program clients. These findings have implications for the development of further income security programs in other primary health care teams across the country.
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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 | 0.144 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".