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Record W1543074450 · doi:10.1002/ev.20076

Framing the Capacity to Do and Use Evaluation

2014· article· en· W1543074450 on OpenAlexaff
J. Bradley Cousins, Swee C. Goh, Catherine Elliott, Isabelle Bourgeois

Bibliographic record

VenueNew Directions for Evaluation · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité du Québec en OutaouaisUniversity of Ottawa
Fundersnot available
KeywordsFraming (construction)ConceptualizationSituatedConstruct (python library)Capacity buildingOrganizational changeSociologyManagement scienceKnowledge managementPublic relationsComputer sciencePolitical scienceEconomics

Abstract

fetched live from OpenAlex

Abstract The construct of organizational evaluation capacity is a concept that is receiving increasing attention in theoretical and research‐based literature. It is situated within a stream of inquiry that has come to be known as evaluation capacity building (ECB). This chapter reviews evolving conceptions of ECB and recent research and theory in the area. A conceptualization of organizational capacity for evaluation is explicated. The framework addresses not only the capacity to do but also the capacity to use evaluation. This framework has evolved within our ongoing research program and has also informed other research activities focusing on the integration of evaluation into organizational culture. This chapter concludes with a discussion of implications for ongoing research and practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.041
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0050.060
Scholarly communication0.0180.017
Open science0.0020.012
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.337
GPT teacher head0.522
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainEvaluation
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

Citations96
Published2014
Admission routes1
Has abstractyes

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