Pio Garcia

In this paper we study the geometrical structure of some polytopes appearing in the study of families of non-additive measures using toric ideals and Gröbner bases. Toric ideals and Gröbner bases are tools appearing in Computational Algebra when dealing with ideals in the ring of polynomials in several variables, and they have been applied for obtaining both the faces and a triangulation of a polytope whose vertices are integer-valued. In this paper we provide examples on which we compare these tools with other ones: order polytopes and the polytope of 2-additive measures. Finally, we derive the combinatorial structure of the subfamily of 2-additive k-ary capacities.

The discovery-justification distinction stands as a pivotal issue within 20th-century philosophy of science. It subtly underpins many foundational topics and concepts pertinent to our comprehension of knowledge. Thomas Kuhn's contributions are indispensable in this regard, with his critiques playing a pivotal role in shaping both his initial model of scientific progress and its subsequent revisions. Kuhn addressed this dichotomy head-on in the first of his Thalheimer Lectures, presented in 1984. In this paper, we revisit Pablo Melogno's (2019) examination of Kuhn's engagement with this theme. Concurring with Melogno, our analysis extends his interpretation by exploring Larry Laudan's objections to certain research programs focused on a logic of discovery. We further scrutinize specific assumptions about discovery heuristics that have been misinterpreted within Laudan's methodological framework, particularly the one stemming from Herbert Simon's pioneering work. By synthesizing these perspectives, we aim to set up a preliminary framework for a more refined understanding of how history and philosophy of science inform the epistemic practices of agents operating with bounded rationality.

The discovery-justification distinction stands as a pivotal issue within 20th-century philosophy of science. It subtly underpins many foundational topics and concepts pertinent to our comprehension of knowledge. Thomas Kuhn's contributions are indispensable in this regard, with his critiques playing a pivotal role in shaping both his initial model of scientific progress and its subsequent revisions. Kuhn addressed this dichotomy head-on in the first of his Thalheimer Lectures, presented in 1984. In this paper, we revisit Pablo Melogno's (2019) examination of Kuhn's engagement with this theme. Concurring with Melogno, our analysis extends his interpretation by exploring Larry Laudan's objections to certain research programs focused on a logic of discovery. We further scrutinize specific assumptions about discovery heuristics that have been misinterpreted within Laudan's methodological framework, particularly the one stemming from Herbert Simon's pioneering work. By synthesizing these perspectives, we aim to set up a preliminary framework for a more refined understanding of how history and philosophy of science inform the epistemic practices of agents operating with bounded rationality.

In this article we propose an analysis of the controversy between Geoffrey Jefferson and Alan Turing in terms of a Kuhnian account of thought experiments. In this account, the main task is not to evaluate intuitions or (only) to rearrange concepts. Instead, we propose that the main task is to construct scenarios by proposing relevant experiences in which shared assumptions and conflicting lines of inquiry can be made explicit. From this perspective, we can understand the arguments and assumptions in the Jefferson-Turing thinking machine controversy.

We present PhrasIS, a benchmark dataset composed of natural occurring Phrase pairs with Inference and Similarity annotations for the evaluation of semantic representations. The described dataset fills the gap between word and sentence-level datasets, allowing to evaluate compositional models at a finer granularity than sentences. Contrary to other datasets, the phrase pairs are extracted from naturally occurring text in image captions and news headlines. All the text fragments have been annotated by experts following a rigorous process also described in the manuscript achieving high inter annotator agreement. In this work we analyse the dataset, showing the relation between inference labels and similarity scores. With 10K phrase pairs split in development and test, the dataset is an excellent benchmark for testing meaning representation systems.

Background Moral distress appears when a healthcare professional is not able to carry out actions in accordance with their professional ethical standards. The Moral Distress Scale-Revised is the most widely used to assess levels of moral distress, but it is not validated in Spanish. The aim of the study is to validate the Spanish version of the Moral Distress Scale – utilised within a sample of Spanish healthcare professionals treating COVID–19 patients. Methods The original (english) and the portuguese and french versions of the scale were translated into spanish by native or bilingual researchers and reviewed by an academic expert in ethics and moral philosophy as well as by a clinical expert. Research design: Descriptive cross-sectional study carried out using a self-reporting online survey. The data was collected between June- November 2020. A total of 661 professionals responded to the survey (N = 2873). Participants: healthcare professionals with more than two weeks of experience treating COVID–19 patients at the end of their life and working in the public sector of the Balearic Islands Health Service (Spain). Analyses included descriptive statistics, competitive confirmatory factor analysis, evidence on criterion-related validity and estimates of reliability. The study was approved by the Research Ethics Committee at the University of Balearic Islands. Results An unidimensional model in which a general factor of moral distress explained by 11 items of the Spanish version of the MDS–R scale was an adequate representation of the data: χ 2 (44) = 113.492 (p 0.001); Comparative Fit Index = 0.965; Root Mean Square Error of Approximation = 0.079[0.062,0.097]; and Standarized Root Mean-Square = 0.037. Evidence of reliability was excellent: Cronbach’s alpha = 0.886 and McDonald’s omega = 0.910. Moral distress was related to discipline, with nurses having statistically significant higher levels than physicians. Additionally, moral distress successfully predicted professional quality of life, with higher levels of moral distress being related to poorer quality of life. Conclusions The Spanish version of Moral Distress Scale–Revised can be used as a reliable and valid measurement tool for the evaluation of moral distress experienced by health professionals. This tool will be highly useful for managers and applicable to a variety of healthcare professionals and settings.

In his paper, Juan Vicente Mayoral presents various aspects of Kuhn’s thought from a historical perspective. Besides the interesting approach that Mayoral proposes for several problems, in this commentary I am going to address only the relevance of the individual in Kuhn. This point can be considered a secondary aspect of Mayoral work, but I think it will allow us to address at least some of Mayoral reading strategies. And even when Mayoral makes few references to the role of individuals, in those places their importance and their problematic nature are underlined. I will suggest a way of emphasizing the relevance of the individual and defending what we are going to call a “compatibility account”. By a “compatibility account” I mean a way to obtain a Kuhnian coherent conceptual picture for individuals and communities. The contrast between what we will call a rational and an interpretative individual will be a means to underline a “compatibility account”. While, as we will see, the activity of individuals in a Kuhnian account is mainly tied to variability, I will present a potential extension of this perspective to a, particularly problematic area: the context of discovery.

In 1936, Alan Turing proposed the notion of an automated machine as a model of the computation performed by a human being while only being aided by mechanical resources. Still, it seems that much more can be said about Turing’s own conception of machines in the scope of his later work, both terminologically and conceptually. In this paper we present the terms he used that refer to machines and that according to our understanding are important to give an account of Turing’s concerns and the problems he tackled with after his first recourse to the notion of machine during the late nineteen-thirties. Exploring his usage of such terms we show how it is possible to see an enlargement or extension towards a general notion of machine from the very first automated machine. At the same time, we identify in his work a modelling attitude or stance in which machines can be used as a way to understand and explain a natural or abstract phenomenon.

En los años veinte del siglo pasado se constituye lo que luego se llamó la escuela de Cambridge en bioquímica. Bajo el liderazgo de Frederick Gowland Hopkins este grupo tenía como objetivo primario la consolidación de la naciente bioquímica. Una característica particular de este grupo fue el intento explícito de vincular el trabajo científico con la discusión filosófica. Sin embargo, algunos historiadores como Nils Roll-Hansen han cuestionado en duros términos la manera en la cual estos científicos apelaban a la filosofía. En particular Roll-Hansen ha sugerido que los aspectos filosóficos del trabajo de estos investigadores tendrían un mero carácter propagandístico vinculado con el proyecto de la constitución de la bioquímica como una disciplina. En este trabajo voy a defender que es posible considerar a los principios filosóficos presentados por la escuela de Cambridge como algo más que una mera propaganda para un proyecto institucional. Para esto voy a comparar la relación entre los principios filosóficos y trabajo metodológico propuesto por la escuela de Cambridge con una propuesta contemporánea: el Análisis de Control Metabólico, una perspectiva en el estudio de la bioquímica cuyo trabajo metodológico se suele defender apelando a “principios filosóficos”. A pesar de la distancia temporal entre ambas escuelas, tanto la actitud de apelar a principios filosóficos como el campo de estudio científico son semejantes.In the twenties of the last century, the Cambridge school in biochemistry was established. Under the leadership of Frederick Gowland Hopkins this group had as its primary objective the consolidation of a new science: biochemistry. A particular feature of this group was the explicit attempt to link scientific work with philosophical discussion. However, some historians like Nils Roll-Hansen have harshly questioned the way in which these scientists appealed to philosophy. In particular Roll-Hansen has suggested that the philosophical aspects of the work of these researchers would have to be considered as propaganda, motivated by attempt stablish the biochemistry as a discipline. In this paper I am going to defend that it is possible to consider the philosophical principles presented by the Cambridge school as something more than a propaganda for an institutional project. To this end I am going to compare the relationship between the philosophical principles and methodological work proposed by the Cambridge school with a contemporary proposal: the Metabolic Control Analysis, a perspective in the study of biochemistry whose methodological work is usually defended by appealing to “philosophical principles”. Despite the temporal distance between the two schools, both the attitude of appealing to philosophical principles and their field of scientific study are similar. Key Words: Philosophy of Biochemistry; Metabolic Control Analysis; Cambridge School ARK: ark:/s18537960/2ak06yaaq

In the last years there has been a great improvement in the development of computational methods for combinatorial chemistry applied to drug discovery. This approach to drug discovery is sometimes called a “rational way” to manage a well known phenomenon in chemistry: serendipity discoveries. Traditionally, serendipity discoveries are understood as accidental findings made when the discoverer is in quest for something else. This ‘traditional’ pattern of serendipity appears to be a good characterization of discoveries where “luck” plays a key role. In this sense, some initial failures in combinatorial chemistry are frequently attributed to a naïf appropriation of a “serendipity model” for discovery (a “serendipity mistake”). In this paper we try to evaluate this statement by criticizing its foundations. It will be suggested that the notion of serendipity has different aspects and that the criticism to the first attempts could be understood as a “serendipity mistake.” We will suggest that “serendipity” strategies, a kind of blind search, can be seen sometimes as a “genuine part” of scientific practice. A discussion will ensue about how this characterization can give us a better understanding of some aspects of serendipity discoveries.

From the beginnings of the biochemistry as discipline, the dichotomy between in vivo- in vitro conditions has been in the center of their methodological discussions. With the growing influence of computer simulations - sometimes called "in silico" conditions-, a new methodological problem is added to biochemistry. However, "simulation" could be seen as a core concept that is in fact used in the in vivo - in vitro dichotomy. In this sense, in silico dimension could be considered as a natural extension of the classical dichotomy. From the way in which simulation is used on in vivo-in vitro dichotomy, we also suggest that the general idea of simulation proposed by Hartmann have to be redefined. The intuitive idea of simulation resting on “imitation” relationship, as a “process that imitates another process” (Hartmann 1996), has to be complemented by others methodological concepts like “isolation” or “disruption”.

Scientific practices have been changed by the increasing use of computer simulations. A central question for philosophers is how to characterize computer simulations. In this paper, we address this question by analyzing simulations in biochemistry. We propose that simulations have been used in biochemistry long before computers arrived. Simulation can be described as a surrogate relationship between models. Moreover, a simulative aspect is implicit in the classical dichotomy between in vivo–in vitro conditions. Based on a discussion about how to characterize a simulative aspect in this dichotomy, we will argue that an adequate understanding of computer simulations in biochemistry requires a previous understanding of simulations in experimental contexts