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Record W2014366393 · doi:10.1177/1356389003094006

Evaluability Assessment: A Tool for Incorporating Evaluation in Social Change Programmes

2003· article· en· W2014366393 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.

Bibliographic record

VenueEvaluation · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité de MontréalUniversity of Calgary
Fundersnot available
KeywordsBehaviour changeSocial changeTheory of changeProcess managementPolitical scienceEngineering ethicsManagement scienceSociologyPublic relationsPsychologyEngineeringPsychological intervention

Abstract

fetched live from OpenAlex

In this article we discuss the evaluation of a particular type of health promotion programme where social change is a central theme of programme development, implementation and evaluation. Evaluation of social change programmes requires a politics of accountability and a utilization focus. These require a process of planning evaluations that mirrors the process of programme planning and implementation. Such an approach must be open to the possibility that the demands on evaluation research may change over the lifecycle of the programme. We propose an evaluability assessment framework as a participatory tool for planning evaluations that meet the need for credible evaluative accounts of social change and contribute to social change. This framework is a tool that can be used at any time to plan and review evaluations.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Other designlow
opusno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.118
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1180.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.454
GPT teacher head0.588
Teacher spread0.134 · 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