Towards identifying WhoFundedIt: An assessment of data quality and availability for analyzing research sponsor bias

Schneider, Jodi

Permalink

https://hdl.handle.net/2142/126453 Copy

Description

Title

Towards identifying WhoFundedIt: An assessment of data quality and availability for analyzing research sponsor bias

Author(s)

Schneider, Jodi

Issue Date

2024-07-01

Keyword(s)

• Scientometrics
• Funding
• Sponsorship
• Bias
• Data quality

Date of Ingest

2025-03-15T15:17:23-05:00

Abstract

Funders impact the knowledge produced (Gläser & Velarde, 2018). Particularly, industry sponsorship can affect the outcomes of research (Lundh et al., 2018). Consequently, managing financial conflicts of interest has become important in clinical medicine (Torgersonet al., 2022). However, determining in the aggregate who funded research on a given topic, and the type of research funder, is currently difficult. Assessing the extent and nature of industry funding is particularly important for assessing the risk of bias in research. Scholars in agnotology describe how "socially constructed ignorance" such as "manufactured certainty" (Leefmann, 2021; Pinto, 2017) has resulted from industry tactics (Goldberg & Vandenberg, 2021) such as tobacco industry lawyers’s involvement in selecting the research to be funded externally (Bero et al., 1995) as well as within the company (Hanauer et al., 1995). Philosophers of science have argued that a scholarly community can become biased without any individual being biased, a phenomenon they refer to as "Experimentation by industrial selection" (Holman & Bruner, 2017). Funding acknowledgement data is increasingly available from sources such as Crossref, Dimensions, Lens, Scopus, and Web of Science (Kramer & de Jonge, 2022), though with varying data quality (Álvarez-Bornstein et al., 2017; Kramer & de Jonge, 2022; Liu, 2020; Liu et al., 2020). In Crossref, only about 14% of data of records on COVID-19 research had a funder identifier (Mugabushaka et al., 2022). WhoFundedIt is a digital library application being developed to provide an interface to visualize who funds research on a specific topic. Given any set of DOIs, our current prototype retrieves funding information from Crossref. Examining past case studies (Golderet al., 2020), data analyses of industry funding (Álvarez-Bornstein & Bordons, 2019), and The Science for Profit Typology (Legg et al., 2021) will be useful in the ongoing development and evaluation of WhoFundedIt.

Has Part

https://github.com/infoqualitylab/WhoFundedIt-app

Series/Report Name or Number

International Conference on the Science of Science and Innovation

Type of Resource

• text
• still image

Genre of Resource

conference poster

Language

eng

Sponsor(s)/Grant Number(s)

NSF 2046454 CAREER: Using network analysis to assess confidence in research synthesis

Owning Collections