Scepticism About Scepticism or the Very Idea of a Global ‘Vat-Language’

This paper aims to motivate a scepticism about scepticism in contemporary epistemology. I present the sceptic with a dilemma: On one parsing of the BIV (brain-in-a-vat) scenario, the second premise in a closure-based sceptical argument will turn out false, because the scenario is refutable; on another parsing, the scenario collapses into incoherence, because the sceptic cannot even save the appearances. I discuss three different ways of cashing out the BIV scenario: ‘Recent Envatment’ (RE), ‘Lifelong Envatment’ (LE) and ‘Nothing But Envatment’ (NBE). I show that RE scenarios are a kind of ‘local’ sceptical scenario that does not pose a significant threat to the possibility of perceptual knowledge as such. I then go on to consider the more radical (or global) LE and NBE scenarios, which do undermine the possibility of perceptual knowledge of an ‘external’ world by positing that it is conceivable that one has always been envatted and, hence, trapped in a ‘global’ illusion. I start by assuming that we could be in such a scenario (LE or NBE) and then spell out what we would need to presuppose for such scenarios to be capable of being actual. Drawing on some central insights from Wittgenstein’s anti-private language considerations, I show that the truth of a global scepticism would presuppose the possibility of a private ‘vat-language’, a notion that cannot be rendered coherent. But, if so, then neither can the sceptical scenarios that presuppose such a conception.

     

Llamas use social information from conspecifics and humans to solve a spatial detour task

Animal Cognition - Learning by observing others (i.e. social learning) is an important mechanism to reduce the costs of individual learning. Social learning can occur between conspecifics but also...     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

All's well that ends well? Outcome bias in pilots during instrument flight rules

The objective of the present study was to examine if the Outcome Bias also occurs in pilots flying under instrument flight rules (IFR). In a scenario-based survey, 60 pilots evaluated weather-related decisions made by hypothetical pilots. Participants rated the decisions as better, less risky, and regarded the probability that they would have made the same decision as higher when they were followed by a positive outcome, than when they were followed by a negative outcome. This effect showed likewise for novice pilots and for experienced pilots. These findings could be relevant for the flight-related decision-making of pilots, which sometimes is affected by the decisions made by third-party pilots. In particular, decisions made by other pilots that have led to positive outcomes might be hastily followed, whereas those that have led to negative outcomes might be hastily rejected.     

Autobiographical memory impairment in chronic schizophrenia: Significance and clinical correlates

Previous studies of autobiographical memory (AM) in schizophrenia yielded a reduction of specificity, richness of details and conscious recollection, which indicate both, quantitative and qualitative AM changes. However, their associations with psychopathological symptoms and neuropsychological deficits were not resolved. Therefore, we sought to investigate AM with respect to psychopathology and neuropsychology in patients with chronic schizophrenia to rule out the influence of different courses of the disease. AM of four lifetime periods was examined in 75 patients and 50 healthy controls by using a semi-structured interview. The recalled episodes were rated for memory specificity. Subsequently, one single event of each period of life was rated for details and experiential aspects of reliving (originality, vividness/visual imagery, emotional re-experiencing and emotional valence). When contrasted with healthy controls, patients recalled a significantly reduced number of episodes and personal semantic facts; moreover, memory specificity of AM was significantly lower in patients than controls. While the richness of details calculated for single events showed only minor, non-significant group differences, vividness and emotional re-experiencing were significantly less pronounced in the patient group. Along with this, AM performance correlated significantly with negative symptoms including apathy as well as verbal memory and executive functions. Our results underline the significance of overgenerality as a key feature of AM in schizophrenia as well as a dissociation between intact number of details of single events and reduced vividness and emotional re-experiencing. The extent of negative symptoms including apathy and impairments of verbal memory/executive functions may explain AM deficits in chronic schizophrenia.     

Factor analysis by generalized least squares

Aitken's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are seale free and asymptotically efficient. The estimates are computed by a rapidly converging Newton-Raphson procedure. A new technique is used to deal with Heywood cases effectively.The work on this project was done when the first author was Research Statistician at Educational Testing Service, Princeton, N. J. The second author was in part supported by a grant from the Research Committee of the University of Wisconsin Graduate School. The authors wish to thank Michael Browne for many helpful comments and Marielle van Thillo for valuable assistance in the numerical computations.     

An individual difference model for the multidimensional analysis of preference data

A model for the analysis of paired comparison data is presented which combines features of the BTL-model with features of the Unfolding model. The model is metric, mathematically tractable, and has an exact algebraic solution. Since it is multidimensional and allows for individual differences, it is thought to be more realistic for some choice situations than either the Thurstone model or the BTL-model. No claim is made that the present model will be appropriate for all conceivable choice situations. Rather, it is argued that the fact that it is explicitly falsifiable is a point in its favor.This work was supported by a grant of the United States Public Health Service (1 R03 MH19139 01 MSM) and a David Ross (XR) grant of the Purdue Research Foundation (PRF 2132), both of which are gratefully acknowledged. We also owe thanks to Dr. Terry Cooper, whose careful scrutiny of an earlier draft of this paper allowed us to reduce the number of errors from n to n-1.     

Some new results on factor indeterminacy

Some relations between maximum likelihood factor analysis and factor indeterminacy are discussed. Bounds are derived for the minimum average correlation between equivalent sets of correlated factors which depend on the latent roots of the factor intercorrelation matrix . Empirical examples are presented to illustrate some of the theory and indicate the extent to which it can be expected to be relevant in practice.