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Arts-based evaluation of the Communities ChooseWell program

2024· article· en· W4402297732 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEvaluation and Program Planning · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsThe artsContext (archaeology)Program evaluationSpace (punctuation)Process (computing)SociologyPsychologyPublic relationsComputer sciencePolitical scienceGeographyPublic administration

Abstract

fetched live from OpenAlex

Arts-based evaluation is an effective and fun way to engage people and uncover meaningful, valid results. In this project, an arts-based approach was used to gain an understanding of the effects the Communities ChooseWell Program has had according to the Champions’ experiences. We wanted to identify what changes, if any, has Communities ChooseWell fostered through the past 10 years? This evaluation was completed using an arts-based approach which allowed us to explore varied long-term effects in different contexts. The creative process allowed for an open approach not predetermining the nature of potential effects. It also gave the participants space to identify what matters the most according to the ChooseWell Champions. This evaluation was in addition to evaluation requirements from the ChooseWell programs funder. In this article we will first present the context of evaluation and state our positionality. We will then present the methodology and methods. Finally, we will present and discuss the results and recommendations. • An arts-based evaluation of the Communities ChooseWell Program in Alberta. • Art is included in data collection, data analysis, and presenting the findings. • Participants reflected and created a painting then collectively designed a quilt. • Quilting was used to present the findings. • Evaluation Question: What changes, if any, has Communities ChooseWell fostered through the past 10 years?

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)0.029
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.495
GPT teacher head0.633
Teacher spread0.137 · 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