Ioannis Votsis

Is Structure Not Enough

This paper counters an objection raised against one of Bertrand Russells lesser‐known epistemological views, viz. “structural realism” (SR). In short, SR holds that at most we have knowledge of the structure of the external (i.e., physical) world. M. H. A. Newmans allegedly fatal objection is that SR is either trivial or false. I argue that the accusation of triviality is itself empty since it fails to establish that SR knowledge claims are uninformative. Moreover, appealing to Quines notion of ontological relativity, I suggest that far from being false, SR knowledge claims seem to be the most that we can hope for.

The upward path to structural realism

In a recent PSA paper (2001a), as well as some other papers (1995, 2000, 2001b) and a book chapter (1999, Chapter 7), Stathis Psillos raised a number of objections against structural realism. The aim of this paper is threefold: (1) to evaluate part of Psillos’ offence on the Russellian version of epistemic structural realism (ESR); (2) to elaborate more fully what Russellian ESR involves; and (3) to suggest improvements where it is indeed failing.

The Prospective Stance in Realism

Scientific realists endeavor to secure inferences from empirical success to approximate truth by arguing that, despite the demise of empirically successful theories, the parts of those theories responsible for their success do, in fact, survive theory change. If, as some antirealists have recently suggested, successful theory parts are only identifiable in retrospect, namely, as those that have survived, then the realist approach is trivialized, for now success and survival are guaranteed to coincide. The primary aim of this article is to counter this argument by identifying successful theory parts independently from their survival.

Saving the intuitions: polylithic reference

My main aim in this paper is to clarify the concepts of referential success and of referential continuity that are so crucial to the scientific realism debate. I start by considering the three dominant theories of reference and the intuitions that motivate each of them. Since several intuitions cited in support of one theory conflict with intuitions cited in support of another something has to give way. The traditional policy has been to reject all intuitions that clash with a chosen theory. A more radical policy, tied to some experimental philosophers, has called for the rejection of any evidential role for intuitions. I explore a largely ignored third alternative, i.e. saving intuitions (and their evidential role) even when they are at odds. To accommodate conflicting intuitions different sets of internally consistent (yet externally inconsistent) intuitions are taken to lend credence to different concepts of reference. In the current context, this means that the concepts of referential success and referential continuity are not monolithic. They are what I call ‘polylithic’. This paper is as much about meta-philosophical concerns with the role of intuitions as it is about reference and the scientific realism debate. Regarding the former I hope that a blueprint will emerge for similar projects in other philosophical domains. Regarding the latter, I hope that polylithicity helps disentangle claims about referential success and continuity in the scientific realism debate by making perspicuous which concepts are best equipped to evaluate the realist’s epistemic claims against the historical record of science.

Data meet theory: up close and inferentially personal

In a recent paper James Bogen and James Woodward denounce a set of views on confirmation that they collectively brand ‘IRS’. The supporters of these views cast confirmation in terms of Inferential Relations between observational and theoretical Sentences. Against IRS accounts of confirmation, Bogen and Woodward unveil two main objections: (a) inferential relations are not necessary to model confirmation relations since many data are neither in sentential form nor can they be put in such a form and (b) inferential relations are not sufficient to model confirmation relations because the former cannot capture evidentially relevant factors about the detection processes and instruments that generate the data. In this paper I have a two-fold aim: (i) to show that Bogen and Woodward fail to provide compelling grounds for the rejection of IRS models and (ii) to highlight some of the models’ neglected merits.

Ad Hoc Hypotheses and the Monsters Within

Science is increasingly becoming automated. Tasks yet to be fully automated include the conjecturing, modifying, extending and testing of hypotheses. At present scientists have an array of methods to help them carry out those tasks. These range from the well-articulated, formal and unexceptional rules to the semi-articulated and variously understood rules-of-thumb and intuitive hunches. If we are to hand over at least some of the aforementioned tasks to machines, we need to clarify, refine and make formal, not to mention computable, even the more obscure of the methods scientists successfully employ in their inquiries. The focus of this essay is one such less-than-transparent methodological rule. I am here referring to the rule that ad hoc hypotheses ought to be spurned. This essay begins with a brief examination of some notable conceptions of ad hoc-ness in the philosophical literature. It is pointed out that there is a general problem afflicting most such conceptions, namely the intuitive judgments that are supposed to motivate them are not universally shared. Instead of getting bogged down in what ad hoc-ness exactly means, I shift the focus of the analysis to one undesirable feature often present in alleged cases of ad hoc-ness. I call this feature the ‘monstrousness’ of a hypothesis. A fully articulated formal account of this feature is presented by specifying what it is about the internal constitution of a hypothesis that makes it monstrous. Using this account, a monstrousness measure is then proposed and somewhat sketchily compared with the minimum description length approach.

Making Contact with Observations

Jim Bogen and James Woodward’s ‘Saving the Phenomena’, published only 20 years ago, has become a modern classic. Their centrepiece idea is a distinction between data and phenomena. Data are typically the kind of things that are publicly observable or measurable like “bubble chamber photographs, patterns of discharge in electronic particle detectors and records of reaction times and error rates in various psychological experiments” (p. 306). Phenomena are “relatively stable and general features of the world which are potential objects of explanation and prediction by general theory” and are typically unobservable (Woodward 1989, p. 393). Examples of the latter category include “weak neutral currents, the decay of the proton, and chunking and recency effects in human memory” (Bogen and Woodward 1988, p. 306). Theories, in Bogen and Woodward’s view, are utilised to systematically explain and predict phenomena, not data (pp. 305–306). The relationship between theories and data is rather indirect. Data count as evidence for phenomena and the latter in turn count as evidence for theories. This view has been further elaborated in subsequent papers (Bogen and Woodward 1992, 2005; Woodward 1989) and is becoming increasingly influential (e.g., Basu 2003; Psillos 2004; Mauricio Suarez 2005).

Reconstructing Scientific Theory Change by Means of Frames

This paper has two aims. The first is to show the usefulness and intuitiveness of frame theory in reconstructing scientific classification systems. The second is to employ such reconstructions in order to make headway in the scientific realism debate and, more specifically, in the question concerning scientific theory change. Two case studies are utilised with the second aim in mind. The first concerns the transition from the phlogiston theory to the oxygen theory of combustion, while the second concerns the transition from the caloric theory to the kinetic theory of heat. Frame-theoretic reconstructions of these theories reveal substantial structural continuities across theory change. This outcome supports a structural realist view of science, according to which successful scientific theories reveal only structural features of the unobservable world.

Editorial introduction to scientific realism quo vadis? Theories, structures, underdetermination and reference

The papers collected in this special issue are written versions of talks delivered at the Theoretical Frameworks and Empirical Underdetermination workshop which we organised at the University of Duesseldorf on April 1 1-12 2008. Early in the summer of 2007 we were still immersed in the planning stages of the workshop. At the time our main concern was to invite philosophers that were making and would continue to make significant contributions to the scientific realism debate. With this aim in mind, we prepared a list of invitees. One of the names at the top was that of Peter Lipton. His work on inference to the best explanation had established him as one of the most prominent and formidable defenders of scientific realism. When Peter accepted the invitation our confidence in the workshops prospects was greatly enhanced. Alas it was not meant to be. Peter unexpectedly passed away in November 2007. His absence from the workshop was strongly felt not least because quite a few of the participants had known Peter both on a professional as well as on a personal basis. David Papineau was drafted in as a replacement. Since David had a long and entwined history with Peter he was entrusted with the honourable task of delivering a eulogy on the opening day of the workshop. We are very thankful to David for delivering a moving eulogy as well as for agreeing to replace Peter at such short notice. We would like to dedicate this special issue of Synthese to the memory of Peter Lipton, a fellow philosopher and to some of us a dear friend. To help the reader navigate this collection we have decided to divide its 1 3 papers into four themes: (i) theory-development, approximate truth and reference (ii)

Unification through Confirmation

The connection between unification and confirmation has been underappreciated. Although seminal works in the literature allude to this connection, they typically fail to provide critical details. Moreover, in the same works the burden of analysing the concept of unification falls on the concepts of understanding and explanation. I argue that the prospects of this approach appear bleak as the latter concepts, at least as they are traditionally construed, are opaque and not readily amenable to an objective treatment. As an alternative, I shift the entire burden of the analysis to confirmational concepts, offering not just a novel account of unification but, more importantly, something that has been virtually missing from the literature, namely a quantitative measure.