Évaluation de l'incidence du financement public de la recherche universitaire québécoise dans le domaine de la biotechnologie
Bibliographic record
Abstract
Cette recherche traitera de l’impact du financement public et prive de la recherche universitaire quebecoise dans le domaine de la biotechnologie. Plusieurs articles analysent deja en detail les types de collaboration entre universites, firmes et laboratoires gouvernementaux. Cependant, peu d’entre eux s’interessent aux deux problematiques suivantes, soit l’impact du financement initial des projets et l’evolution de la connaissance generee par la recherche et les collaborations entre chercheurs. En utilisant les donnees tirees de la base de donnees d’articles scientifiques Scopus d’Elsevier et du Systeme d’information sur la recherche universitaire (SIRU) detaillant le financement recu en termes de contrats et subventions, nous construisons une base de donnees du financement recu par les chercheurs universitaires et de leurs publications. Le critere de selection pour l’extraction d’un article est d’avoir au moins un co-auteur canadien. En utilisant les liens entre co-auteurs, nous construisons un reseau base sur les chercheurs au cours de la periode 1985-2005 a l’aide d’un logiciel developpe pour automatiser l’integration complexe de nos differentes sources de donnees de facon a generer une matrice d’analyse. A la suite de la construction du reseau, nous proposons un modele temporel de l’impact du financement de la recherche universitaire et des caracteristiques du reseau sur la production scientifique mesuree par la publication d’articles scientifiques. Les resultats suggerent que le financement individuel a un impact positif sur la production scientifique et que la categorisation du financement est necessaire pour comprendre l’impact reel sur la publication d’articles scientifiques. Le nombre croissant d’articles publies aujourd’hui peut etre explique de facon plus precise par les contrats recus depuis les trois dernieres annees et par les subventions recues depuis les cinq dernieres annees. L’environnement universitaire semble avoir un impact specifique sur le nombre de publications des chercheurs affilies.---------- ABSTRACT This study focuses on the impact of public and private financing of academic research in the Quebec biotechnology sector. Prior research analyzes the economic impact of university-industry-government collaborations but fewer studies are concerned with the initial funding and the resulting evolution of knowledge creation and dispersion by researchers. Using the information contained in Elsevier’s Scopus scientific articles database and the Quebec Systeme d’information sur la recherche universitaire (SIRU) which gives a detailed account of grants and contracts obtained by each researcher, we build a database of the funding received by individual academic researchers and their scientific publications. The selection criterion for an article to be extracted is that at least one Canadian scientist is a co-author. Using co-authorship links, we create the network of individual scientists for the period 1985-2005 with the help of custom built software whose purpose is to automate the complex integration of our multiple data sources and generate an analysis matrix. Following the network construction, we propose a time-related model of the impact of academic R&D financing and network structure on research output measured by the number of papers. Results suggest that individual funding has a positive effect on research output and that funding categorization is crucial in understanding the impacts on scientific publications. The increasing number of papers published today can be better explained by the contracts received in the past 3 years horizon and by the grants received in the past 5 years horizon. The university environment seems to have a specific effect on the level of research output for the biotechnology sector.
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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 | 0.014 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".