Towards CR<sup>2</sup> evaluation: Culturally ‐reflexive and ‐responsive evaluation in crises times and beyond
Bibliographic record
Abstract
Abstract More than ever, health services evaluators are in high demand. In such context, evaluation deliverables are time‐ and/or culturally‐sensitive. For the target communities or for those with an interest in the evaluation, the priority is to make sure their voice is prominently featured in evaluation deliverables. This priority coincides with a context where evaluators need to negotiate their positionality, in a context where evaluation deliverables are time‐ and/or culturally‐sensitive. Beyond the mere inclusion of health service users as evaluation stakeholders, how do evaluators position themselves in these discussions? How do they meaningfully navigate this new paradigm in health services evaluation? This issue refers to intangible processes, which can be supported through both natural predisposition and the acquisition of specific skills. Core competencies for credentialled evaluators now all feature the importance of self‐awareness and reflexive thinking; as well as the demonstration of appropriate and respectful verbal and non‐verbal communication skills, and the capacity to identify practice communities' needs and capacity to participate, while recognising, respecting, and responding to aspects of diversity. Culturally‐responsive evaluation is a promising approach to reconcile the world of evaluators and diverse practice communities. Recently, the concept of cultural humility—a reflexive learning process initially designed for frontline workers—has also gained important traction. In this perspective paper, we reflect on the added‐value of combining these two approaches (hence, CR2 evaluation—reflexive and responsive) to fulfil the promise of patient and community‐centeredness in health service evaluation.
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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 | 0.103 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.037 | 0.015 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".