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Enregistrement W3196994941 · doi:10.1108/lht-04-2021-0136

Measuring the funding landscape of COVID-19 research

2021· article· en· W3196994941 sur OpenAlex

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Notice bibliographique

RevueLibrary Hi Tech · 2021
Typearticle
Langueen
DomaineMathematics
ThématiqueCOVID-19 epidemiological studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCoronavirus disease 2019 (COVID-19)ChinaBibliometricsWeb of scienceLibrary science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Ranking (information retrieval)PublishingPolitical scienceRegional scienceGeographyBusinessMEDLINEMedicineComputer scienceInformation retrieval

Résumé

récupéré en direct d'OpenAlex

Purpose The purpose of the study is to map the funding status of COVID-19 research. The various aspects, such as funding ratio, geographical distribution of funded articles, journals publishing funded research and institutions that sponsor the COVID-19 research are studied. To visualize the country collaboration network and research trends/hotspots in the field of COVID-19 funded research, keyword analysis is also performed. The open-access (OA) status of the funded research on COVID-19 is also discussed. Design/methodology/approach The leading indexing and abstracting database, i.e. Web of Science (WoS), was used to retrieve the funded articles published on the topic COVID-19. The scientometric approach, more particularly “funding acknowledgment analysis (FAA),” was used to study the research funding. Findings A total of 5,546 publications of varied nature have been published on COVID-19, of which 1,760 are funded, thus indicating a funding ratio of 32%. China is the leading producer of funded research (760, 43.182%) on COVID-19 followed by the USA (482, 27.386%), England (179, 10.17%), Italy (119, 6.761%), Germany (107, 6.08%) and Canada (107, 6.08%). China is also in lead in terms of the funding ratio (60.94%). However, the funding ratio of the USA (31.54%) is at 11th rank behind Canada (40.68%), Germany (34.18%) and England (35.87%). The USA occupies a central position in the collaboration network having the highest score of articles with other countries ( n = 489), with the USA–China collaboration ranking first ( n = 123). National Natural Science Foundation of China (NSFC) is the largest source of funding for COVID-19 research, supporting 342 (19.432%) publications, followed by the United States Department of Health Human Services (DHHS) and National Institute of Health (NIH), USA with 211 (11.989%) and 200 (11.364%) publications, respectively. However, China's National Key Research and Development Program achieves the highest citation impact (80.24) for its funded publications. Journal of Medical Virology, Science of the Total Environment and EuroSurveillance are the three most prolific journals publishing 63 (3.58%), 35 (1.989%) and 32 (1.818%), respectively, of the sponsored research articles on the COVID-19. A total of 3,138 institutions produce funded articles with Huazhong University of Science Technology and Wuhan University from China at the forefront publishing 92 (5.227%) and 83 (4.716%) publications, respectively. The funded research on COVID-19 is largely available in OA mode (1,674, 95.11%) and mainly through the Green and Bronze routes. The keyword clustering reveals that the articles mainly focus on the impact, structure and clinical characteristics of the virus. Research limitations/implications The study's main limitation is that the results are based on the publications indexed by WoS, which has limited coverage compared to other databases. Moreover, all the funding agencies do not require or authors miss to acknowledge funding sources in their publications, which ultimately undermines the number of funded publications. The research publications on COVID-19 are also proliferating; thus, the study's findings shall be valid for a minimum period. Practical implications The funding of research on the COVID-19 is highly essential to accelerate innovative research and help countries fight against the global pandemic. The study's findings reflect the efforts made by nations and institutions to remove the financial and accessibility hurdles. It not only underscores the lead of the USA in the research on COVID-19, but also shows China as a forerunner in sponsoring the research, thus, helping to know the contribution of nations toward understanding the dynamics of pandemic and controlling it. The study will help healthcare practitioners and policymakers recognize the areas that remain the focus of sponsored research on COVID-19 and other left-out areas that need to be taken up and thus may help in policy formulation. It further highlights the impact of prolific funding agencies so that efforts may be initiated to increase the impact and thereby the returns of investment. The study can help to map the scientific structure of COVID-19 through the lens of funded research and recognize core inclinations of its development. Overall, a comprehensive analysis has been performed to present the detailed characteristics of sponsored research on emerging area of COVID-19, and it is informative, useful and one of its kind on the theme. Originality/value The study explores the funding support of research on COVID-19 and its other aspects, along with the mode of availability.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,018
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,390
Score d'incertitude au seuil0,990

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,018
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,611
Tête enseignante GPT0,481
Écart entre enseignants0,130 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle