Perspective research entrepreneurship output performance in 1992–2009
Bibliographic record
Abstract
This paper aims on research entrepreneurship output performance from 1992 to 2009. Data are based on the online version of ISI Web of Science from 1992 to 2009 focusing on SSCI publishing paper that topic is to respect on entrepreneurship. This study synthetically uses the bibliometric method, study entrepreneurship institute and country analysis, source title, author keyword, and keyword plus analysis, to map global research entrepreneurship during the period of 1992–2009. The data shows research entrepreneurship performance top fifty countries ranking is USA, UK, Canada, Germany, Netherlands, Spain, Sweden, Australia, France, Italy, Finland, Israel, Singapore, Denmark and Switzerland. The top ten publication institutes is Univ Nottingham, UK; Indiana Univ, USA; Max Planck Inst Econ, Germany; Univ Minnesota, USA; Babson Coll, USA; Harvard Univ, USA; Rensselaer Polytech Inst, USA; Univ Illinois, USA; Erasmus Univ, Netherlands and Case Western Reserve Univ, USA. The result finding four issues of innovation, entrepreneurship capital, corporate culture, and economic growth are the most popular issues in the research entrepreneurship field in the future. This investigation will help researchers realize the panorama of global research entrepreneurship trend, and establish further research direction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".