MétaCan
Menu
Back to cohort
Record W4366382532 · doi:10.3138/cjpe.31132

Moving Beyond the Buzzword: A Framework for Teaching Culturally Responsive Approaches to Evaluation

2017· article· en· W4366382532 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsConceptual frameworkCompetence (human resources)Cultural competenceSociologyDomain (mathematical analysis)Knowledge managementComputer scienceEngineering ethicsPsychologyPedagogySocial psychologySocial scienceEngineering

Abstract

fetched live from OpenAlex

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 responsive 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 domains: 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.064
metaresearch head score (Gemma)0.060
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0640.060
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.641
GPT teacher head0.560
Teacher spread0.081 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it