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Record W4366446383 · doi:10.3138/cjpe.26.001

In Search of a Balanced Canadian Federal Evaluation Function: Getting to Relevance

2011· article· en· W4366446383 on OpenAlexaffvenueabout
Robert P. Shepherd

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsRelevance (law)Function (biology)TreasuryArgument (complex analysis)CriticismGovernment (linguistics)Public relationsPublic policyPolitical sciencePublic administrationManagement scienceComputer scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract: In April 2009, the Treasury Board Secretariat enacted a new Evaluation Policy replacing the previous 2001 version. This new policy has generated much discussion among the evaluation community, including the criticism that it has failed to repair the many shortcomings the function has faced since it centralized in 1977. This article reviews the history of the federal function as to why shortcomings persist and makes two assertions. First, if program evaluation is going to maintain its relevance, it will have to shift its focus from the individual program and services orientation to understanding how these programs and services relate to larger public policy objectives. Second, if program evaluation is to assume a whole-of-government approach, then evidentiary forms must be constructed to serve that purpose. The author makes the argument that evaluation must be far more holistic and calibrative than in the past; this means assessing the relevance, rationale, and effect of public policies. Only in this way can the function both serve a practical managerial purpose and be relevant to senior decision-makers.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.161
GPT teacher head0.401
Teacher spread0.239 · 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; a candidate call from one teacher head, not a consensus.

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

Citations8
Published2011
Admission routes3
Has abstractyes

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