Bibliometric Analysis and Funding Success to Evaluate an Organization’s Research Grant Decisions
Notice bibliographique
Résumé
Title: Bibliometric Analysis and Funding Success to Evaluate an Organization’s Research Grant Decisions Objectives The Manitoba Medical Services Foundation (MMSF), a non-profit medical foundation that has provided nearly $20 million to support and fund research since 1974, sought to evaluate the subsequent output of both its successful and unsuccessful operating grant applicants. The foundation, which focuses on supporting new researchers, worked with the Library to determine whether its grant review process was successful in selecting the best candidates from 2008 to the 2012 competitions. Methods Using information up to 2014 for the five years of grants, which totaled $1,912,300 in funding, an analysis was first completed for all successful and unsuccessful grant applications. The analysis focused on two areas: publication history and funding history. Scopus – one of the largest databases in the world and a resource committed to eliminating author identification issues – was employed to determine the number of published articles and the h-index for each researcher. The funding databases of the three largest federal granting agencies in the country were searched to determine whether a researcher had subsequently obtained other grants. The bibliometric and funding data were statistically analyzed to assess the impact of a researcher’s initial grant result on their future publication output and funding success, as well as the local multiplier effect for the granting organization. Results Statistical analyses clearly demonstrated that those researchers who received funding from the MMSF went on to have greater academic productivity than unsuccessful candidates. Specifically, successful candidates had a greater number of publications, a higher h-index, larger amount of funding from the major Canadian research granting organizations, and greater odds of receiving funds as either co-investigators or lead principal investigators. Analyses also showed that successful applicants were ultimately very successful in bringing future external funding back to the province, with a local multiplier effect of 10:1 (i.e., for every $1 spent on Manitoba-based researchers, $10 returns to the community). Conclusions This research demonstrated that the current process used by MMSF is successful at selecting individuals who subsequently go on to become high-performing researchers. These researchers are ultimately more productive and obtain more funding than those individuals that are not selected. Furthermore, this project demonstrates a new way for Libraries to use metrics to assist organizations or institutions as they are called upon to demonstrate their value and impact on the community.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,052 | 0,180 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,133 | 0,157 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».