MétaCan
Menu
Back to cohort
Record W2242738494 · doi:10.25916/sut.26256047

A longitudinal comparative study of the role of entrepreneurship in research commercialisation performance: Australia, UK and USA

2005· article· en· W2242738494 on OpenAlexaboutno aff
Murray Gillin, John Yencken

Bibliographic record

VenueSwinburne Research Bank (Swinburne University of Technology) · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipRegional sciencePolitical scienceEconomic geographyGeographyEconomic growthEconomics

Abstract

fetched live from OpenAlex

Research commercialisation surveys are now available fm Australia for the FY 2000 and 2002. The paper reviews longitudinal comparative data for research commercialisation performance in Australia, the United Kingdom, Canada and the USA. Commercialisation performance measures with a specific focus on entrepreneurial spin-off companies are discussed and performance ,comparisons have been made based on research expenditure in US dollars adjusted for purchasing power parity. The conclusions from these analyses suggest that Australian public agency performance in generation of spin-offs, that is New Technology Small Firms, per unit of research expenditure adjusted for purchasing power parity has been comparable in recent years to and in some sectors superior to that in the other countries reviewed. However, Australian university revenue from intellectual property licensing royalties and research contracts has been below that of the other countries studied. The analysis suggests that this results from both a demand side problem , low business investment in R&D and hence low technology absorptive capacity, and a supply side problem, that is lack of time and lack of incentive to academic researchers to develop contacts with and meet the expectations of industry and other research users for technology that works.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.355
Teacher spread0.198 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueSwinburne Research Bank (Swinburne University of Technology)Same topicEntrepreneurship Studies and InfluencesFrench-language works237,207