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

Measuring the funding landscape of COVID-19 research

2021· article· en· W3196994941 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLibrary Hi Tech · 2021
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus 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

Abstract

fetched live from 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.

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.

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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.611
GPT teacher head0.481
Teacher spread0.130 · 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