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Record W4366453138 · doi:10.3138/cjpe.28.007

The Five Cs for Innovating in Evaluation Capacity Building: Lessons from the Field

2013· article· en· W4366453138 on OpenAlexaffvenueabout
Evangeline Danseco

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsOntario Centre of Excellence for Child and Youth Mental Health
Fundersnot available
KeywordsExcellenceCoachingCuriosityCapacity buildingCourageKey (lock)Field (mathematics)Public relationsBusinessPsychologyKnowledge managementPolitical scienceEconomic growthManagementEconomicsComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract: Innovation is essential in addressing complex evaluation capacity building (ECB) efforts that include a host of interacting, nonlinear, adaptive, and dynamical individual and organizational level factors. This article highlights five key ingredients in fostering innovation in ECB, based on evaluation capacity building efforts of the Ontario Centre of Excellence for Child and Youth Mental Health. For the past 5 years, 87 organizations have participated in an integrated ECB program combining funding, training, and coaching support. The five key ingredients to fostering innovation in ECB are curiosity, courage, communication, commitment, and connection.

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.

How this classification was reachedexpand

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)0.035
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.563
GPT teacher head0.558
Teacher spread0.004 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2013
Admission routes3
Has abstractyes

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