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Record W2006398869 · doi:10.1080/08109028.2011.641385

Paradox and potential: trends in science policy and practice in Canada and New Zealand

2011· article· en· W2006398869 on OpenAlexfundaboutno aff
Janet Halliwell, Willie Smith

Bibliographic record

VenuePrometheus · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsBRICChinaFace (sociological concept)Science policyPolitical scienceIdeologyGlobalizationPoliticsEconomic growthRegional scienceSociologyPublic administrationEconomicsSocial science

Abstract

fetched live from OpenAlex

Over the last 30 years, Canada and New Zealand have redirected their science and research systems to meet changing national priorities, and in response to global trends and needs. They have shared a common effort to transform their traditionally resource-based economies. Both are committed to the creation of knowledge-based economies that can compete internationally in the face of massive globalization and the rise of the BRIC nations (Brazil, Russia, India and China). Research, and science and technology, are seen as the primary drivers towards this goal. Canada and New Zealand developed science systems shaped by their common British heritage. In recent years, their science systems have undergone fundamental changes, yet they continue to share many evolving trends, highlighted in the ideas, methods, values and norms identified as Mode 2, in The New Production of Knowledge. These trends, however, have been shaped by different policies and different institutional arrangements, different theoretical perspectives and different political ideologies.

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)0.021
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.783

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.045
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.019
Science and technology studies0.0160.026
Scholarly communication0.0240.008
Open science0.0030.006
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0080.000

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 head0.150
GPT teacher head0.433
Teacher spread0.283 · 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 designQualitative
DomainIncentives
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

Citations11
Published2011
Admission routes2
Has abstractyes

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