Rinse and Repeat: Understanding the Value of Replication across Different Ways of Knowing

Penders, Bart; Holbrook, J. Britt; Rijcke, Sarah de

doi:10.3390/publications7030052

Cited by 43 publications

(42 citation statements)

References 34 publications

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“…A similar claim about the importance of the local research context has recently been made based on conceptual considerations rather than empirical analyses. This second component of what I call the new localism in the replication crisis debate targets the idea of replicability as a universal standard (de Rijcke and Penders 2018; Leonelli 2018; Nadin 2018; Penders et al 2019).…”

Section: Replicability As a Local Standardmentioning

confidence: 99%

“…Such plurality is often seen as an inherent feature of this type of research, and not as a sign of immaturity or flawed research practice. When addressing complex issues like, for instance, migration and what it means for society on a global scale, diverse positions are needed to develop sensible solutions that can work (Penders et al 2019). This type of research cannot lead to 'the' single answer that scientists can arrive at with a highly standardized protocol.…”

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

“…This type of research cannot lead to 'the' single answer that scientists can arrive at with a highly standardized protocol. To impose a strict replicability criterion would therefore be counterproductive, as it would endanger the production of diverse insights and hypotheses in these fields (de Rijcke and Penders 2018; Penders et al 2019).…”

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

“…The idea is to enable readers of the report to judge how factors such as the emotional state of the researcher might have affected the results and interpretations that were reported. In line with this, Penders and colleagues have highlighted that there are other 'technologies of accountability'apart from replicationthat researchers can use to ensure the production of reliable and trustworthy findings (Penders et al 2019). Similarly, Jim Bogen has pointed out, based on an indepth study of nineteenth century research in physiology, that replications might not always be necessary to assess the reliability of existing evidence, as researchers have other ways of doing so (Bogen 2001).…”

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

“…A replication drive that is too broad could also lead researchers to pursue research protocols that ignore the inherent variation of the local context studied (Leonelli 2018). Furthermore, it might lead scientists to abandon the disciplinary standards of their field and lead to a reduction in the diversity of the findings and interpretations they produce (Penders et al 2019). 8 The conclusions we can draw from Fanelli's empirical analysis are similar: if the extent of the replication problem is not the same across science or even sub-disciplines, then broad changes to how research is funded and regulated might not be justified, especially as they could create harm in fields that don't need correcting in the first place.…”

Section: The Implications Of the New Localismmentioning

confidence: 99%

See 4 more Smart Citations

The limits of replicability

Güttinger

2020

Euro Jnl Phil Sci

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Discussions about a replicability crisis in science have been driven by the normative claim that all of science should be replicable and the empirical claim that most of it isn't. Recently, such crisis talk has been challenged by a new localism, which argues a) that serious problems with replicability are not a general occurrence in science and b) that replicability itself should not be treated as a universal standard. The goal of this article is to introduce this emerging strand of the debate and to discuss some of its implications and limitations. I will in particular highlight the issue of demarcation that localist accounts have to address, i.e. the question of how we can distinguish replicable science from disciplines where replicability does not apply.

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Section: Replicability As a Local Standardmentioning

confidence: 99%

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

Section: Working With Different Questions and Setupsmentioning

confidence: 99%

Section: The Implications Of the New Localismmentioning

confidence: 99%

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The limits of replicability

Güttinger

2020

Euro Jnl Phil Sci

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Data sharing in modeling and simulation of biomechanical systems in interdisciplinary environments

Villota‐Narvaez,

Bleiler,

Röhrle

2024

GAMM-Mitteilungen

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All digital objects that result from the modeling and simulation field are valid sets of research data. In general, research data are the result of intense intellectual activity that is worth communicating. This communication is an essential research practice that, whether with the aim of understanding, critiquing or further developing results, smoothly leads to collaboration, which not only involves discussions, and sharing institutional resources, but also the sharing of data and information at several stages of the research process. Data sharing is intended to improve and facilitate collaboration but quickly introduces challenges like reproducibility, reusability, interoperability, and standardization. These challenges are deeply rooted in an apparent reproducibility standard, about which there is a debate worth considering before emphasizing how the modeling and simulation workflow commonly occurs. Although that workflow is almost natural for practitioners, the sharing practices still require special attention because the principles (known as FAIR principles) that guide research practices towards data sharing also guide the requirements for machine actionable results. The FAIR principles, however, do not address the actual implementation of the data sharing process. This implementation requires careful consideration of characteristics of the sharing platforms for benefiting the most of the data sharing activity. This article serves as an invitation to integrate data sharing practices into the established routines of researchers and elaborates on the perspectives, and guidelines surrounding data sharing implementation.

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Epistemic Functions of Replicability in Experimental Sciences: Defending the Orthodox View

Sikorski

Andreoletti

2023

Found Sci

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Replicability is widely regarded as one of the defining features of science and its pursuit is one of the main postulates of meta-research, a discipline emerging in response to the replicability crisis. At the same time, replicability is typically treated with caution by philosophers of science. In this paper, we reassess the value of replicability from an epistemic perspective. We defend the orthodox view, according to which replications are always epistemically useful, against the more prudent view that claims that it is useful in very limited circumstances. Additionally, we argue that we can learn more about the original experiment and the limits of the discovered effect from replications at different levels. We hold that replicability is a crucial feature of experimental results and scientists should continue to strive to secure it.

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Rinse and Repeat: Understanding the Value of Replication across Different Ways of Knowing

Cited by 43 publications

References 34 publications

The limits of replicability

The limits of replicability

Data sharing in modeling and simulation of biomechanical systems in interdisciplinary environments

Epistemic Functions of Replicability in Experimental Sciences: Defending the Orthodox View

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