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Record W2071194841 · doi:10.3152/147154302781781119

Evaluation of governments’ scientific output: a bibliometric profile of Canada

2002· article· en· W2071194841 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueScience and Public Policy · 2002
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsGovernment (linguistics)Production (economics)Political sciencePublic administrationQuality (philosophy)DisciplineRegional scienceSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

Over the last 15 years, heavy budgetary restrictions imposed on government departments have, according to some authors, compromised the scientific production of public R&D laboratories. This article uses bibliometric data to look at the scientific production of the Canadian Federal intramural R&D. The data show beyond any doubt the major importance of the Federal Government's contribution to the advancement of Canadian science — over a third of Canadian publications in several disciplinary specialities. Moreover, in the disciplines in which they have distinguished themselves the most, federal researchers have, in terms of the quality of their publications, no cause to be envious of Canadian researchers in general. However, this article reveals that the share of Canadian scientific publications coming from public laboratories has decreased over the last 15 years.

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)0.093
metaresearch head score (Gemma)0.206
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication
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 score0.907
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0930.206
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.3740.835
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0030.001
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 head0.602
GPT teacher head0.531
Teacher spread0.071 · 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