Robust Evidence and Secure Evidence Claims

Abstract

Many philosophers have claimed that evidence for a theory is better when multiple independent tests yield the same result, i.e., when experimental results are robust. Little has been said about the grounds on which such a claim rests, however. The present essay presents an analysis of the evidential value of robustness that rests on the fallibility of assumptions about the reliability of testing procedures and a distinction between the strength of evidence and the security of an evidence claim. Robustness can enhance the security of an evidence claim either by providing what I call second-order evidence, or by providing back-up evidence for a hypothesis. (Whewell 1989, 138-160; Peirce 1992, 29, 138;Wimsatt 1981;Hacking 1983;Trout 1993;Culp 1994Culp , 1995 have claimed that evidence for a theory is better when multiple independent tests yield the same (convergent) positive result, i.e., when experimental results are robust. Robert Hudson has recently denied this claim (Hudson 1999). The evidential value of robust evidence has been argued for from a Bayesian perspective (Franklin and Howson 1984). This essay seeks to demonstrate the evidential value of robustness from a non-Bayesian point of view and to identify some limits to the evidential value of robustness. Introduction. Many philosophersThe present analysis also draws attention to two distinctions that writers on evidence do not typically draw. First, I distinguish between first-order and second-order evidence in order to shed light on the use of data to

Intervention, causal reasoning, and the neurobiology of mental disorders: Pharmacological drugs as experimental instruments

“…14;Chang, 2004, ch. 1;Staley, 2004;Stegenga, 2009). These analyses maintain that a scientific hypothesis or theory is "robust" (i.e., well-confirmed) when multiple lines of (at least partially) independent research all point to a common result.…”

Confirmation and Robustness of Climate Models

“…4 It is against this background of differing model constructions that the core structure occurs and causes the robust property to appear, and it is the degree of this variety of fit for which the model has been verified that determines how confident we should be in the causal connection. Weisberg deems this to be a part of robustness analysis, but it is a step beyond the usual robustness analysis, which involves only inferences about the robust property and not about the model(s) that generated that robust property (e.g., Staley 2004;Woodward 2006). As such, it fits more naturally as a subtype of variety of evidence inferences, to which we can apply the probabilistic results demonstrating its confirmatory value.…”

“…Under other interpretations of robustness, philosophers have found that while it reveals important relationships among models, it does not actually confirm those models. Robustness may, for example, be used to eliminate accidents in measurement (Staley 2004), but it is not perceived as a positive confirmatory virtue. In our case, however, the core structure is compared across a variety of assumptions or model backgrounds, thus providing a variety of evidence for the core structure causing or being correlated with the model outcome.…”

Derivational Robustness and Indirect Confirmation

“…According to William Wimsatt (1981), robustness allows identification of the assumptions that really 'drive' the robust result (see also Staley 2004;Kuorikoski, Lehtinen, and Marchionni 2010). Elizabeth Lloyd (2009; presents the argument from the variety of evidence and provides case studies in climate research, but she does not go into the details of how this happens.…”