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Record W2992485618 · doi:10.3138/cjpe.024.001

The Lay of the Land: Evaluation Practice in Canada in 2009

2009· article· en· W2992485618 on OpenAlexaffvenueabout
Benoît Gauthier, Gail V. Barrington, Sandra L. Bozzo, Kaireen Chaytor, Alice Dignard, Robert Lahey, Robert Malatest, James C. McDavid, Greg Mason, John Mayne, Nancy L. Porteous, S. Basu Roy

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsPublic Health Agency of CanadaUniversity of VictoriaMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsCLARITYCertificationPublic relationsSophisticationPsychologyBusinessPolitical scienceSociologyLawSocial science

Abstract

fetched live from OpenAlex

Abstract: A group of 12 evaluation practitioners and observers takes stock of the state of program evaluation in Canada. Each contributor provides a personal viewpoint, based on his or her own experience in the field. The selection of contributors constitutes a purposive sample aimed at providing depth of view and a variety of perspectives. Each presentation highlights one strength of program evaluation practiced in Canada, one weakness, one threat, and one opportunity. It is concluded that Canadian evaluation has matured in many ways since 2003 (when a first panel scan was conducted): professional designation is a reality; the infrastructure is stronger than ever; organizations are more focused on results. Still, evaluation is weakened by lacunas in advanced education and professional development, limited resources, lack of independence, rigidity in evaluation approaches, and lack of self-assessment. While the demand for evaluation and evaluators appears on the rise, the supply of evaluators and the financial resources to conduct evaluations are not. The collective definition of the field of evaluation still lacks clarity. There is also reassurance in looking toward the future. With increased appetite for evaluation, evaluators could make a real difference, especially if evaluators adopt a more systemic view of program action to offer a global understanding of organizational effectiveness. The implementation of a Certified Evaluator designation by CES is a major opportunity to position evaluation as a more credible discipline.

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)0.037
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.014
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 science0.0010.000
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 head0.227
GPT teacher head0.519
Teacher spread0.292 · 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 designObservational
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

Citations12
Published2009
Admission routes3
Has abstractyes

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