Moving Beyond the Buzzword: A Framework for Teaching Culturally Responsive Approaches to Evaluation
Bibliographic record
Abstract
The terms cultural responsiveness and cultural competence have become ubiquitous in many fields of social inquiry, including in evaluation. The discourse surrounding these issues in evaluation has also increased markedly in recent years, and the terms can now be found in many RFPs and government-based evaluation descriptions. We have found that novice evaluators are able to engage culturally re-sponsive approaches to evaluation at the conceptual level, but are unable to translate theoretical constructs into practice. In this article we share a framework for teaching culturally responsive approaches to evaluation. The framework includes two do-mains: conceptual and methodological, each with two interconnected dimensions. The dimensions of the conceptual domain include locating self and social inquiry as a cultural product. The dimensions of the methodological domain include formal and informal applications in evaluation practice. Each of the dimensions are linked to multiple domains within the Competencies for Canadian Evaluation practice. We discuss each and provide suggestions for activities that align with each of the dimensions.Les termes sensibilité culturelle et compétence culturelle sont mainten-ant omniprésents dans de nombreux domaines d’enquête sociale, notamment en évaluation. Le discours entourant ces questions en évaluation s’est aussi intensifié de façon marquée au cours des dernières années et ces termes sont maintenant présents dans de nombreuses demandes de proposition et descriptions d’évaluation émanant d’organismes gouvernementaux. Nous avons trouvé que les évaluateurs débutants sont en mesure de concevoir des approches d’évaluation culturellement adaptées, mais sont incapables de transférer ces notions théoriques à la pratique. Dans le présent article, nous décrivons un cadre pour l’enseignement d’approches évaluatives qui soient culturellement sensibles. Le cadre inclut deux sphères – conceptuelle et méthodologique – chacune ayant deux dimensions interconnectées. Les dimensions de la sphère conceptuelle implique de positionner l’évaluateur et le processus de recherche comme un produit culturel. Les dimensions de la sphère mé-thodologique comprennent des applications formelles et informelles pour la pratique
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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 | 0.066 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".