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Evaluation of RT&D: from 'prescriptions for justifying' to 'user-oriented guidance for learning'

2010· article· en· W2063748664 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Evaluation · 2010
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsHierarchySubject (documents)Frame (networking)Work (physics)Production (economics)Computer scienceKnowledge managementSociologyOperations researchPolitical scienceEngineeringEconomicsLibrary scienceTelecommunicationsMicroeconomics

Abstract

fetched live from OpenAlex

The measurement and evaluation of research, technology and development (RT&D) has gone through phases over the past 50 years. Over time, high-level measures such as total expenditures on R&D, overall citations and patent production have given way to more contextualized metrics recognizing the inherent differences in innovation subject areas and the need to show mission achievement. This article shows how recently proposed Canadian Academy of Health Sciences (CAHS) metrics were adapted to help frame a case study conducted by the Canadian Cancer Society Research Institute (CCSRI). Early results suggest that the framework provides a useful structure to display both a hierarchy of results focused on mission goals, and to build an attributable RT&D and innovation story over time. With this work and other recent developments, evaluation appears poised to go beyond retrospective justification and to become a fully legitimate part of strategic learning for RT&D initiatives.

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.

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)0.338
metaresearch head score (Gemma)0.637
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3380.637
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0290.063
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.921
GPT teacher head0.738
Teacher spread0.183 · 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