MétaCan
Menu
Back to cohort
Record W2337090609 · doi:10.3138/cjpe.022.005

A Participatory Approach to the Development of an Evaluation Framework: Process, Pitfalls, and Payoffs

2007· article· en· W2337090609 on OpenAlex
Mary Frances MacLellan-Wright, San Patten, Añiela dela Cruz, Annette Flaherty

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsAlberta HealthAlberta Community Council on HIVPublic Health Agency of Canada
Fundersnot available
KeywordsCitizen journalismParticipatory evaluationParticipatory GISProcess (computing)Participatory developmentProcess managementKnowledge managementBusinessSociologyManagement scienceComputer scienceEconomicsSocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract: Much literature exists on participatory approaches to developing and implementing program evaluation. Little is documented, however, about participatory approaches to developing an evaluation framework. This article reports a case study of implementation of a participatory evaluation approach and examines the results in light of participatory evaluation theory. A participatory approach was used to develop a provincial evaluation framework for a unique, collaborative community/provincial/federal funding program for community-based HIV/AIDS service organizations in Alberta, Canada. The participatory process resulted in significant capacity building, mutual learning, and relationship development, as well as a comprehensive and user-friendly provincial evaluation framework. The purpose of this article is to share our process, the pitfalls, and the payoffs to our participatory approach in developing an evaluation framework.

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)0.074
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0740.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.522
GPT teacher head0.565
Teacher spread0.042 · 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