The aim of this paper is to address the semantic issue of the nature of the representation I and of the transcendental designation, i.e., the self-referential apparatus involved in transcendental apperception. The I think, the bare or empty representation I, is the representational vehicle of the concept of transcendental subject; as such, it is a simple representation. The awareness of oneself as thinking is only expressed by the I: the intellectual representation which performs a referential function of the spontaneity of a thinking subject. To begin with, what exactly does Kant mean when he states that I is a simple and empty representation? Secondly, can the features of the representation I and the correlative transcendental designation explain the indexical nature of the I? Thirdly, do the Kantian considerations on indexicality anticipate any of the semantic elements or, if nothing else, the spirit of the direct reference theory?

A variety of theorists have recently argued against the explanation of the semantic content of a sentence as a minimal proposition claiming that intentional aspects of the context are often needed to obtain a minimal proposition. Minimalists such as Borg, however, still defend intention-insensitive minimal propositions for sentences in a narrow context and provide solutions or dissolutions against incompleteness objections. In this paper, we show that these putative defences of propositionalism do not serve to avoid some additional genuine objections which arise from compositional context-sensitivity. We aim to show that there are complex expressions which compositionally demand intention-sensitive pragmatic effects in a mandatory way and, for that reason, they provide us with evidence against the type of propositionalism that substantiates the defence of semantic minimalism.

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

Scientific research is based on the division of cognitive labour: every scientist has to trust that other colleagues have checked whether the items that are taken as knowledge, and she cannot check by herself, are reliable enough. I apply ideas from the field known as ‘information economics’ (the study of economic interactions where some agents are better informed than others) to analyse the scientists’ incentives to produce items of knowledge of an ‘adequate’ quality, under the assumption that a big part of what one observes in her empirical research is not available for the readers of the paper. I also discuss some criticisms to this ‘marketization’ of science studies.

The aim of the paper is to clarify the concept of scientific ignorance: what is it, what are its sources, and when is it epistemically detrimental to science. While some sources of scientific ignorance come inevitably with the process of knowledge acquisition, others are deliberately created. The former includes selection processes, inductive reasoning, and cognitive biases, while the latter includes scientific fraud. Another important source of scientific ignorance appears when scientists introduce methodological biases through micro-decisions in the research process. I provide three examples from medical research to illustrate this point. I argue further that methodological biases present a challenge, in so far as they are no easily classifiable as deliberate: they might also be the result of entrenched research practices within a scientific community. Strategies to identify and prevent methodological biases in research should take into account such difference.

I argue that the aim of belief and the aim of science are both knowledge. The ‘aim of belief’ is to be identified with the product of a properly functioning cognitive system. Science is an institution that is the social, functional analogue of a cognitive system, and its aim is the same as that of belief. In both cases it is knowledge rather than true belief that is the product of proper functioning.

Contemporary interdisciplinary research is often described as bringing some important changes in the structure and aims of the scientific enterprise. Sometimes, it is even characterized as a sort of Kuhnian scientific revolution. In this paper, the analogy between interdisciplinarity and scientific revolutions will be analysed. It will be suggested that the way in which interdisciplinarity is promoted looks similar to how new paradigms were described and defended in some episodes of revolutionary scientific change. However, contrary to what happens during some scientific revolutions, the rhetoric with which interdisciplinarity is promoted does not seem to be accompanied by a strong agreement about what interdisciplinarity actually is. In the end, contemporary interdisciplinarity could be defined as being in a ‘pre-paradigmatic’ phase, with the very talk promoting interdisciplinarity being a possible obstacle to its maturity.

With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management (KM): second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli (2014, 2016), Efstathiou (2012, 2016) and Hislop (2013) in our analysis of the use of KM in semantic systems biology. Through an empirical philosophical account of KM-enabled biological research, we argue that KM helps produce new first-order biological knowledge that did not exist before, and which could not have been produced by traditional means. KM work is enabled by conceiving of ‘knowledge’ as an object for computational science: as explicated in the text of biological articles and computable via appropriate data and metadata. However, these founded knowledge concepts enabling computational KM risk focusing on only computationally tractable data as knowledge, underestimating practice-based knowing and its significance in ensuring the validity of ‘manageable’ knowledge as knowledge.

We argue against the claim that the employment of diagrams in Euclidean geometry gives rise to gaps in the proofs. First, we argue that it is a mistake to evaluate its merits through the lenses of Hilbert’s formal reconstruction. Second, we elucidate the abilities employed in diagram-based inferences in the Elements and show that diagrams are mathematically reputable tools. Finally, we complement our analysis with a review of recent experimental results purporting to show that, not only is the Euclidean diagram-based practice strictly regimented, it is rooted in cognitive abilities that are universally shared.

The aim of this paper is to explore the possibility that at least some ontological dispute are better understood as what David Plunkett and Timothy Sundell have called ‘metalinguistic negotiations’. I will take the debate between the dominant approaches of realism and anti-realism (especially fictionalism) about the ontological status of scientific models as a case-study. I will argue that such a debate is best seen as normatively motivated, insofar as a normative and non-factual question may be involved in it: how ought the relevant piece of language to be used? Even though I will generally assess the prospects for a broadly deflationist approach, I shall outline a sense in which such a dispute can be recast as ‘minimally substantive’.

I offer an analysis of the concept of scientific innovation. When research is innovated, highly novel and useful elements of investigation begin to spread through a scientific community, resulting from a process which is neither due to blind chance nor to necessity, but to a minimal use of rationality. This, however, leads to tension between two claims: (1) scientific innovation can be explained rationally; (2) no existing account of rationality explains scientific innovation. There are good reasons to maintain (1) and (2), but it is difficult for both claims to be accepted simultaneously by a rational subject. In particular, I argue that neither standard nor bounded theories of rationality can deliver a satisfactory explanation of scientific innovations.

During the 19th century, evolutionary models of innovation followed a famous thesis of continuity, according to which methods and explanatory patterns of biology should have an important say in the social sciences. In the 20th century, this thesis was considered unacceptable as part of the sharp separation of biology from the social sciences. Recent advances in the biological sciences suggest a way in which a version of the thesis of continuity can be reinstated, to suggest new ways of explaining innovation in the social sciences. Key kinds of innovation can be explained in terms of the evolution of robust complex systems, interpreted as processes of path creation.

There is a rough, long-term tradeoff between rate of innovation and degree of strong realism in scientific practice, a point reflected in historically changing conceptions of method as they retreat from epistemological foundationism to a highly fallibilistic, modeling perspective. The successively more liberal, innovation-stimulating methods open up to investigation deep theoretical domains at the cost, in many cases, of moving away from strong realism as a likely outcome of research. The crowbar model of method highlights this tension, expressed as the crowbar compromise and the crowbar fallacy. The tools-to-theories heuristic, described and evaluated by Gigerenzer and colleagues, can be regarded as an attempt by some scientific realists to overcome this compromise. Instead, it is an instance of it. Nonetheless, in successful applications the crowbar model implies a modest, instrumental (nonrepresentational) realism.

We offer a novel argument for one-boxing in Newcomb’s Problem. The intentional states of a rational person are psychologically coherent across time, and rational decisions are made against this backdrop. We compare this coherence constraint with a golf swing, which to be effective must include a follow-through after the ball is in flight. Decisions, like golf swings, are extended processes, and their coherence with other psychological states of a player in the Newcomb scenario links her choice with the way she is predicted in a common cause structure. As a result, the standard argument for two-boxing is mistaken.

In order to show how technological innovation and scientific innovation are linked in the course of research in human science, I present an account of a series of innovations made in our laboratory (Distal Glove – Tactos system – Intertact server – Dialtact module). We will see how research on the technical constitution of cognitive and perceptual activities can be associated with a process of innovation. The technical devices present at each stage carry an interpretative framework that prepares the following stages. Devices which were initially developed for the purposes of performing experiments contributed both to scientific inventions and to developments with a practical and social finality.

Jerry Fodor’s arguments for a language of thought (LOT) are largely theoretical. Is there any empirical evidence that supports the existence of LOT? There is. Research on Global Aphasia supports the existence of LOT. In this paper, I discuss this evidence and why it supports Fodor’s theory that there is a language of thought.