Culturally Competent Evaluation for Aboriginal Communities: A Review of the Empirical Literature
Bibliographic record
Abstract
Much of program evaluation is concerned with understanding and improving social programs so that they are ultimately more responsive and more reflective of program participant needs. At the same time, these programs exist and are embedded within specific social, cultural and historical contexts which impact program development, implementation, and eventual outcomes. Evaluations that attempt to address responsiveness to contextual and cultural specificity are often referred to as culturally competent, culturally responsive, inclusive, multicultural, or cross-cultural, among other terms. While there are no agreed upon terminologies, definitions, or even methodologies, what these approaches all share is the recognition that culture and context matter, and that there are no universally agreed upon rules or abstractions that can be applicable in all contexts (Guba & Lincoln, 2005). The recognition of culture and context thus becomes “an explicit criterion rather than an unspoken expectation” (SenGupta, Hopson, & Thompson-Robinson, 2004, p. 15) in evaluations of this type.
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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 | 0.032 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".