Realistic Evaluation and the Process-Tracing Method: A Combined Approach to Scrutinizing Causal Mechanisms
Bibliographic record
Abstract
Abstract: This article proposes a methodological contribution for causal mechanism scrutiny by combining realistic evaluation (RE) and the process-tracing method (PTM). To overcome some limits of RE’s operationalization, the combination RE-PTM reinforces RE by breaking down the causal mechanisms and testing them with PTM. This combination was tested as part of a project for the professional integration of young people in difficulty. We developed a theoretical framework involving the framing of RE and used Bayesian logic to test the RE hypotheses. Semi-structured interviews served as the main evidence source. The results of the study support the fact that the RE-PTM combination can address some RE operationalization challenges. The RE-PTM procedure shows that PTM can provide RE with guidance on how to collect and assess data that support the contribution made by an intervention in achieving the expected outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.099 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".