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

Fetal septal neurons were grown in vitro under glass coverslips. This sandwich culture method significantly increased general neuronal survival, reduced glial proliferation, and permitted the removal of serum from the growth medium after 5 d in vitro. Thereafter, a simple, and completely defined, medium was used, and the effects of NGF, NGF withdrawal, and protein synthesis inhibition were examined on septal cholinergic neurons. NGF added to septal cultures at the time of plating resulted in a threefold increase in the number of cholinergic neurons seen at 14 d in vitro but had no effect on the survival of non-cholinergic cells. Cholinergic neurons identified by staining for AChE, ChAT, and p75NGFR could be maintained in serum-free, NGF-supplemented medium for over 40 d. When NGF was removed and NGF antibodies added to 14-d-old cultures, less than 30% of cholinergic neurons survived a further 4 d, but when NGF was similarly withdrawn from 35-d-old cultures, over 75% of cholinergic neurons survived. Reapplication of NGF after 3 but not after 12 or more hours of NGF withdrawal from 14-d-old cultures prevented the death of most cholinergic neurons. When NGF was withdrawn from 14-d-old cultures in the presence of the protein synthesis inhibitor cycloheximide, over 75% of the cholinergic neurons survived. These findings suggest that septal cholinergic neurons are dependent on NGF for survival only during a critical period of development and that growth factor-regulated developmental cell death may occur in CNS neurons by activation of programmed cell death requiring protein synthesis.

Reports of quantitative experimental results often distinguish between the statistical uncertainty and the systematic uncertainty that characterize measurement outcomes. This paper discusses the practice of estimating systematic uncertainty in High Energy Physics (HEP). The estimation of systematic uncertainty in HEP should be understood as a minimal form of quantitative robustness analysis. The secure evidence framework is used to explain the epistemic significance of robustness analysis. However, the empirical value of a measurement result depends crucially not only on the resulting systematic uncertainty estimate, but on the learning aims for which that result will be used. Philosophically important conceptual and practical questions regarding systematic uncertainty assessment call for further investigation.

No abstract

No abstract