value free ideal
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Martin Carrier

AbstractI address options for providing scientific policy advice and explore the relation between scientific knowledge and political, economic and moral values. I argue that such nonepistemic values are essential for establishing the significance of questions and the relevance of evidence, while, on the other hand, such social choices are the prerogative of society. This tension can be resolved by recognizing social values and identifying them as separate premises or as commissions while withholding commitment to them, and by elaborating a plurality of policy packages that envisage the implementation of different social goals. There are limits to upholding the value-free ideal in scientific research. But by following the mentioned strategy, science can give useful policy advice by leaving the value-free ideal largely intact. Such scientific restraint avoids the risk of appearing to illegitimately impose values on the public and could make the advice given more trustworthy.

Pal Swarup ◽  
Ghosh Sudip

In this essay, I have attempted to defense the possibility of objectivity in case of social science research. It is basically an evaluation of Max Weber’s interpretation in maintaining the possibility of objectivity in social science. There is a long tradition in the philosophy of social science maintaing a sharp distinction between social science and natural science in terms of both goals as well as method; and there is no doubt about that natural sciences have the higher degree of objectivity in comparison with social science. It is not possible to maintain absolute objectivity in case of social science research. But, by following some tricksit is possible to make a social inquiry more reliable and justifiable.This paper aims to improve such tricks as well as such a unique methodology adopted by Max Weber through which it is possible to maintain objectivity in social science as well as to establish social science as a successful science. Keywords: Max Weber, Objectivity, Social Science, Natural Science, Value-free Ideal, Theory-Ladenness, Value-Neutrality

2021 ◽  
pp. 003754972110288
Alejandro Cassini

Some philosophers of science have recently argued that the epistemic assessment of complex simulation models, such as climate models, cannot be free of the influence of social values. In their view, the assignment of probabilities to the different hypotheses or predictions that result from simulations presupposes some methodological decisions that rest on value judgments. In this article, I criticize this claim and put forward a Bayesian response to the arguments from inductive risk according to which the influence of social values on the calculation of probabilities is negligible. I conclude that the epistemic opacity of complex simulations, such as climate models, does not preclude the application of Bayesian methods.

2020 ◽  
Vol 28 (1) ◽  
pp. 89-118
Torbjørn Gundersen

This article contributes to the philosophical debate on values in science by exploring how scientists themselves understand the proper role of moral, political, and social values in expert practice. I present findings from interviews with climate scientists who have participated as authors in the Intergovernmental Panel on Climate Change (IPCC). The climate scientists subscribe to the value-free ideal as a regulative ideal that applies both to the provision of knowledge to policymakers and how they engage with political issues in the public sphere. Yet their views on the moral responsibility of scientists and the aim of providing policy-relevant output challenge the value-free ideal. The article suggests ways in which their views can be relevant to the philosophical discussion.

2019 ◽  
Vol 29 (1) ◽  
pp. 123-143 ◽  
Edwin Koster ◽  
Henk W. de Regt

AbstractWhile a conception of science as value free has been dominant since Max Weber defended it in the nineteenth century, recent years have witnessed an emerging consensus that science is not – and cannot be – completely free of values. Which values may legitimately influence science, and in which ways, is currently a topic of heated debate in philosophy of science. These discussions have immediate relevance for science teaching: if the value-free ideal of science is misguided, science students should abandon it too and learn to reflect on the relation between science and values – only then can they become responsible academics and citizens. Since science students will plausibly become scientists, scientific practitioners, or academic professionals, and their values will influence their future professional activities, it is essential that they are aware of these values and are able to critically reflect upon their role. In this paper, we investigate ways in which reflection on science and values can be incorporated in undergraduate science education. In particular, we discuss how recent philosophical insights about science and values can be used in courses for students in the life sciences, and we present a specific learning model – the so-called the Dilemma-Oriented Learning Model (DOLM) – that allows students to articulate their own values and to reflect upon them.

2018 ◽  
Vol 26 (6) ◽  
pp. 619-657 ◽  
Daniel Steel ◽  
Chad Gonnerman ◽  
Aaron M. McCright ◽  
Itai Bavli

David M. Frank

According to Richard Jeffrey’s value-free ideal, scientists should avoid making value judgments about inductive risks by offering explicit representations of scientific uncertainty to decision-makers, who can use these to make decisions according to their own values. Some philosophers have responded by arguing that higher-order inductive risks arise in the process of producing representations of uncertainty. This chapter explores this line of argument and its limits, arguing that the Jeffreyan value-free ideal is achievable in contexts where methodological decisions introduce minimal higher-order uncertainty and where communications of uncertainty are unlikely to be manipulated or misunderstood by scientists or decision-makers. This chapter illustrates the limits of the Jeffreyan ideal with reference to climate science and argues that the context of climate science is not conducive to the Jeffreyan ideal, so the argument that climate modeling is value-laden due to higher-order inductive risks withstands recent criticisms.

Kevin C. Elliott ◽  
Ted Richards

This concluding chapter provides a roadmap for future studies of inductive risk by drawing attention to three particularly important sets of questions that emerge from Exploring Inductive Risk: (1) the nature of inductive risk, the argument from inductive risk (AIR), and the distinction between the direct and indirect roles for values; (2) the extent to which the AIR can be evaded by defenders of the value-free ideal; and (3) the strategies that the scientific community can employ to handle inductive risk in a responsible fashion. This chapter not only highlights these questions as they emerge in this volume but also shows how they connect with the previous literature on inductive risk.

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