COVID-19 VACCINATION IN THREE SITES IN SASKATCHEWAN: A PATIENT-ORIENTED REALIST EVALUATION
Bibliographic record
Abstract
The purposes of this research were to evaluate the COVID-19 vaccination campaign in three pilot sites (Regina, Saskatoon, Prince Albert) in Saskatchewan and construct program theories for vaccine uptake among the recipients and vaccine delivery by the Saskatchewan Health Authority (SHA) stakeholders who were involved in the planning and delivery of the vaccines. The program theories contain contextual factors and causal mechanisms that influenced vaccine uptake and delivery.\nTraditional evaluations oversimplify characteristics of interventions and the environment surrounding them (1). Finding solutions to complex problems needs a through understanding of the nature of the problem, interventions, and the implementation contexts (2). Problems operate at various levels (individual, local, organizational, societal) which makes the relevant interventions complex (2). Literature has shown that targeted efforts are needed to increase vaccine uptake (3). In a theory-driven realist evaluation, evaluators raise the question of “for whom, under what circumstances, how and why do interventions work or not work?”, and build program theories to answer the question (2,4,5). Realist evaluation requires considerable researcher reflection, creativity, judgment, and inferences (6,7).\nBy using a novel combination of patient-oriented research (POR) strategy and the realist evaluation, three and six initial program theories (IPTs) for the vaccine recipients and the SHA stakeholders, respectively, were developed collaboratively with three patient and family partners (PFPs). We refined and finalized the IPTs into seven program theories (PTs) by collecting insights from six vaccine recipients and six SHA stakeholders via realist evaluation interviews. We identified salient contextual factors that evoked mechanism chains resulting in intermediate outcome of vaccine hesitancy or willingness among the recipients. These contextual factors and causal mechanisms demonstrate the complex reality of Saskatchewan’s COVID-19 vaccination campaign, show causal pathways for vaccine strategies, and help policymakers to enhance vaccination programs for other jurisdictions.
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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 | 0.063 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".