Proprietary Reasons and Joint Action

Some of the reasons one acts on in joint action are shared with fellow participants. But others are proprietary: reasons of one’s own that have no direct practical significance for other participants. The compatibility of joint action with proprietary reasons serves to distinguish the former from other forms of collective agency; moreover, it is arguably a desirable feature of joint action. Advocates of “team reasoning” link the special collective intention individual participants have when acting together with a distinctive form of practical reasoning that purports to put individuals in touch with group or collective reasons. Such views entail the surprising conclusion that one cannot engage in joint action for proprietary reasons. Suppose we understand the contrast between minimal and robust forms of joint action in terms of the extent to which participants act on proprietary reasons as opposed to shared reasons. Then, if the team reasoning view of joint intention and action is correct, it makes no sense to talk of minimal joint action. As soon as the reason for which one participates is proprietary, then one is not, on this view, genuinely engaged in joint action

Research in progress: report on the ICAIL 2017 doctoral consortium

This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences

Domesticating Fears and Fantasies of ‘the East’: integrating the Ottoman legacy within European heritage

'Europe' has no fixed geographical, historical, religious or cultural boundaries. Claims for the existence of European civilization as a discrete construct are continually made yet dissolve on close scrutiny. Here, we examine these claims at one of the grandest points of existential crisis and belonging for Europe, the relationship with the 'Other within': Turkey, the Balkans and Ottoman heritage in Europe. Through a hybrid semiotic and Foucauldian analysis of catalogues of eight high-profile exhibitions in the United Kingdom, Turkey, Belgium and Portugal we argue that an unsettled discursive struggle is at play, in which one 'Europe' articulates 'reconciliation' of profound civilizational difference while another, Ottoman, 'Europe' stakes a claim of right as an intrinsic component of what it means to be European in a contemporary context. We attempt to trace the role of museum marketing in the perennial accommodation/exclusion of the Ottoman Empire as an intrinsic component in the diversity of Europe’s cultural heritage

"I am NN": A Reconstruction of Anscombe's "The First Person"

This paper develops a way of understanding G.E.M. Anscombe’s essay “The First Person”, at the heart of which are the following two ideas: first, that the point of her essay is to show that it is not possible for anyone to understand what they express with “I” as an Art des Gegebenseins—a way of thinking of an object that constitutes identifying knowledge of which object is being thought of; and second, that the argument through which her essay seeks to show this is itself first personal in character. Understanding Anscombe’s essay in this light has the merit of showing much of what it says to be correct. But it sets us the task of saying what it is that we understand ourselves to express with “I” if not an Art des Gegebenseins, and in particular what it is that we understand ourselves to express with sentences with “I” as subject that might seem to express identity-judgments, such as “I am NN”, and “I am this body”

Detection of inconsistencies in geospatial data with geostatistics

Almost every researcher has come through observations that “drift” from the rest of the sample, suggesting some inconsistency. The aim of this paper is to propose a new inconsistent data detection method for continuous geospatial data based in Geostatistics, independently from the generative cause (measuring and execution errors and inherent variability data). The choice of Geostatistics is based in its ideal characteristics, as avoiding systematic errors, for example. The importance of a new inconsistent detection method proposal is in the fact that some existing methods used in geospatial data consider theoretical assumptions hardly attended. Equally, the choice of the data set is related to the importance of the LiDAR technology (Light Detection and Ranging) in the production of Digital Elevation Models (DEM). Thus, with the new methodology it was possible to detect and map discrepant data. Comparing it to a much utilized detections method, BoxPlot, the importance and functionality of the new method was verified, since the BoxPlot did not detect any data classified as discrepant. The proposed method pointed that, in average, 1,2% of the data of possible regionalized inferior outliers and, in average, 1,4% of possible regionalized superior outliers, in relation to the set of data used in the study

Enterovirus D68 in Viet Nam (2009-2015)

Since 1962, enterovirus D68 (EV-D68) has been implicated in multiple outbreaks and sporadic cases of respiratory infection worldwide, but especially in the USA and Europe with an increasing frequency between 2010 and 2014. We describe the detection, associated clinical features and molecular characterization of EV-D68 in central and southern Viet Nam between 2009 and 2015.Enterovirus/rhinovirus PCR positive respiratory or CSF samples taken from children and adults with respiratory/central nervous system infections in Viet Nam were tested by an EV-D68 specific PCR. The included samples were derived from 3 different observational studies conducted at referral hospitals across central and southern Viet Nam between 2009 and 2015. Whole-genome sequencing was carried out using a MiSeq based approach. Phylogenetic reconstruction and estimation of evolutionary rate and recombination were carried out in BEAST and Recombination Detection Program, respectively.EV-D68 was detected in 21/625 (3.4%) enterovirus/rhinovirus PCR positive respiratory samples but in none of the 15 CSF. All the EV-D68 patients were young children (age range: 11.8 - 24.5 months) and had moderate respiratory infections. Phylogenetic analysis suggested that the Vietnamese sequences clustered with those from Asian countries, of which 9 fell in the B1 clade, and the remaining sequence was identified within the A2 clade. One intra sub-clade recombination event was detected, representing the second reported recombination within EV-D68. The evolutionary rate of EV-D68 was estimated to be 5.12E -3 substitutions/site/year. Phylogenetic analysis indicated that the virus was imported into Viet Nam in 2008.We have demonstrated for the first time EV-D68 has been circulating at low levels in Viet Nam since 2008, associated with moderate acute respiratory infection in children. EV-D68 in Viet Nam is most closely related to Asian viruses, and clusters separately from recent US and European viruses that were suggested to be associated with acute flaccid paralysis

Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets