Epistemic luck

In almost any domain of endeavour, successes can be attained through skill, but also by dumb luck. An archer’s wildest shots occasionally hit the target. Against enormous odds, some fair lottery tickets happen to win. The same goes in the case of purely cognitive or intellectual endeavours. As inquirers, we characteristically aim to believe truly rather than falsely, and to attain such standings as knowledge and understanding. Sometimes such aims are attained with commendable competence, but of course, not always. Epistemic luck is a species of luck which features in circumstances where a given cognitive success—in the broadest sense, some form of cognitive contact with reality—is attained in a manner that is (in some to-be-specified sense) interestingly lucky—viz., chancy, accidental or beyond our control. In the paradigmatic case, this involves the formation of a belief that is luckily true, and where the subject plausibly deserves little credit for having gotten things right. Although the literature on epistemic luck has focused predominantly on the relationship between luck and propositional knowledge—which is widely taken to (in some sense) exclude luck—epistemologists are increasingly exploring the compatibility of epistemic luck with other kinds of epistemic standings, such as knowledge-how and understanding

Nota sobre algúnos alimentos arbustivos del clímax- mediterráneo seleccionados por el ciervo: determinación por examen del contenido ruminal en el "cervus elaphus L."

Se estudia los contenidos ruminales de tres ciervos sacrificados durante l!lS estaciones de verano, invierno y primavera, con el fin de determinar qué especies vegetales arbustivas son las consumidas. Se hallan las frecuencias de aparición y a p:utir de éstas su porcentaje. En verano y en primavera es la Phillyrea angustifolia la que alcanza un mayor porcentaje, 20 0/o y 44,87 °/o respectivamente. Mientras que en invierno est:i representado con un 58,25 Ofo por el Quercus ilex con sus frutos

Situational-Context for Virtually Modeling the Elderly

The generalized aging of the population is incrementing the pressure over, frequently overextended, healthcare systems. This situations is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. In this paper we propose an initial approach to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills. The proposed virtual models will also be the basis for further eldercare innovations in sparsely populated regions

Context-aware mobile app for the multidimensional assessment of the elderly,

Rural areas in Europe are presenting a decreasing population density and an increasing age index. These elders usually present multiple diseases that require complex tools to identify the exact cares that they need. Currently, different frameworks can evaluate their functional status and identify the required cares to maintain their Quality of Life, together with the associated cost to the health system. Nevertheless, these frameworks are usually questionnaires that have to be performed by already overloaded professionals. In this paper, we make use of mobile technologies to build a system capable of monitoring the activities of the elderly and analysing these data to assess their functional status. The experiments carried out show us that it correctly evaluates these patients and reduces the effort required by health professionals

Enriched elderly virtual profiles by means of a multidimensional integrated assessment platform

The pressure over Healthcare systems is increasing in most developed countries. The generalized aging of the population is one of the main causes. This situation is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. The authors propose to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills or the costs of implementing such systems by the regional healthcare systems. In this paper, the integration of a multidimensional integrated assessment platform with such virtual profiles is presented. The assessment platform provides and additional source of information for the virtual profiles that is used to better adapt existing systems to the elders needs

A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5_{2.5} concentration

A typical problem in air pollution epidemiology is exposure assessment for individuals for which health data are available. Due to the sparsity of monitoring sites and the limited temporal frequency with which measurements of air pollutants concentrations are collected (for most pollutants, once every 3 or 6 days), epidemiologists have been moving away from characterizing ambient air pollution exposure solely using measurements. In the last few years, substantial research efforts have been placed in developing statistical methods or machine learning techniques to generate estimates of air pollution at finer spatial and temporal scales (daily, usually) with complete coverage. Some of these methods include: geostatistical techniques, such as kriging; spatial statistical models that use the information contained in air quality model outputs (statistical downscaling models); linear regression modeling approaches that leverage the information in GIS covariates (land use regression); or machine learning methods that mine the information contained in relevant variables (neural network and deep learning approaches). Although some of these exposure modeling approaches have been used in several air pollution epidemiological studies, it is not clear how much the predicted exposures generated by these methods differ, and which method generates more reliable estimates. In this paper, we aim to address this gap by evaluating a variety of exposure modeling approaches, comparing their predictive performance and computational difficulty. Using PM$_{2.5}$ in year 2011 over the continental U.S. as case study, we examine the methods' performances across seasons, rural vs urban settings, and levels of PM$_{2.5}$ concentrations (low, medium, high)

The Epistemology of Group Disagreement: An Introduction

This is an introduction to the volume The Epistemology of Group Disagreement (Routledge, forthcoming), (eds.) F. Broncano-Berrocal and J.A. Carter

Deliberation and Group Disagreement

Suppose an inquiring group wants to let a certain view stand as the group's view. But there’s a problem: the individuals in that group do not initially all agree with one another about what the correct view is. What should the group do, given that it wants to settle on a single answer, in the face of this kind of intragroup disagreement? Should the group members deliberate and exchange evidence and then take a vote? Or, given the well-known ways that evidence exchange can go wrong, e.g., by exacerbating pre-existing biases, compromising the independence of individual judgments, etc., should the group simply take a vote without deliberating at all? While this question has multiple dimensions to it—including ethical and political dimensions—we approach the question through an epistemological lens. In particular, we investigate to what extent it is epistemically advantageous and disadvantageous that groups whose members disagree over some issue use deliberation in comparison to voting as a way to reach collective agreements. Extant approaches in the literature to this ‘deliberation versus voting’ comparison typically assume there is some univocal answer as to which group strategy is best, epistemically. We think this assumption is mistaken. We approach the deliberation versus voting question from a pluralist perspective, in that we hold that a group’s collective endeavor to solve an internal dispute can be aimed at different, albeit not necessarily incompatible, epistemic goals, namely the goals of truth, evidence, understanding, and epistemic justice. Different answers to our guiding question, we show, correspond with different epistemic goals. We conclude by exploring several ways to mitigate the potential epistemic disadvantages of solving intragroup disagreement by means of deliberation in relation to each epistemic goal