The concept of mechanism from a realist approach: a scoping review to facilitate its operationalization in public health program evaluation
Bibliographic record
Abstract
BACKGROUND: Public health interventions are complex by nature, and their evaluation requires unpacking their intervention logic and their interactions with open social systems. By focusing on the interrelationships between context, mechanism, and outcome, Pawson and Tilley's realist approach appears a promising innovation for public health-related evaluation works. However, and as expected of any methodological innovation, this approach is being constructed gradually by answering the multiple challenges to its operationalization that fall in its path. One of these challenges, users of this approach agree on, is the necessity of clarifying its key concept of mechanism. METHOD: We first collected the definitions of mechanism from published works of Pawson and colleagues. Secondly, a scoping review was conducted to identify the ones quoted by users of the realist approach for evaluating public health interventions (1997-2012). We then appraised the clarity and precision of this concept against the three dimensions defined by Daigneault and Jacobs "term, sense and referent." RESULTS: Of the 2344 documents identified in the scoping review, 49 documents were included. Term: Users of the realist approach use adjectives qualifying the term mechanism that were not specifically endorsed by Pawson and colleagues. Sense: None of the attributes stated by Pawson and colleagues has been listed in all of the documents analyzed, and some contributions clarified its attributes. Referent: The concept of mechanism within a realist approach can be ascribed to theory-based evaluation, complex social interventions, and critical realism. CONCLUSION: This review led us to reconsider the concept of mechanism within the realist approach by confronting the theoretical stance of its proponents to the practical one of its users. This resulted in a clearer, more precise definition of the concept of mechanism which may in turn trigger further improvements in the way the realist approach is applied in evaluative practice in public health and potentially beyond. A mechanism is hidden but real, is an element of reasoning and reactions of agents in regard to the resources available in a given context to bring about changes through the implementation of an intervention, and evolves within an open space-time and social system of relationships.
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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 | 0.575 | 0.664 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.089 | 0.054 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.031 | 0.039 |
| Open science | 0.010 | 0.019 |
| Research integrity | 0.015 | 0.012 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".