Gallacher, John and Webster, Chris (2022) High Quality Research Environments. [Preprint]
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Abstract
A major challenge facing all research communities is creating and sustaining high quality research environments. A model describing strategic social structures that constrain knowledge production suggests that targeting these structures will have greater impact than addressing issues surrounding individual lab cultures, as important as these are.
A literature search identified five common themes underlying bioscience research environments comprising collaboration, data processing, confidence in data and scientists, trust, user-led development, and a deep commitment to public benefit. Club theory was used to develop a model describing the social structures that constrain and contextualise research environments.
It is argued that collaboration underlies impactful science and that this is hindered by high transaction costs, and the benefits associated with competition. These combined with poorly defined property rights surrounding publicly funded data limit the ability of data markets to operate efficiently. Although the science community is best placed to provide solutions for these issues, incentivisation by funding agencies to increase the benefits of collaboration will be an accelerator. Given the complexity of emerging datasets and the collaborations need to exploit them, trust-by-design solutions are suggested. The underlying ‘glue’ that holds this activity together is the aesthetic and ethical value-base underlying good science.
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| Item Type: | Preprint | |||||||||
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| Keywords: | research, environment, club theory, collaboration | |||||||||
| Subjects: | General Issues > Science and Society General Issues > Values In Science |
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| Depositing User: | Dr Sarah Bauermeister | |||||||||
| Date Deposited: | 05 Dec 2022 14:25 | |||||||||
| Last Modified: | 05 Dec 2022 14:25 | |||||||||
| Item ID: | 21518 | |||||||||
| Subjects: | General Issues > Science and Society General Issues > Values In Science |
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| Date: | 2 December 2022 | |||||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/21518 |
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