Some of my collaborators have been: Michele Friend, Luis Estrada-González, Gabrielle Ramos-García, Josafat I. Hernández and Moisés Macías-Bustos.
Check out their amazing work!
Check out their amazing work!
REFEREED ARTICLES[10] “A Methodological Shift in Favor of (Some) Paraconsistency in the Sciences" in Logica Universalis (2022).
Winner of the ‘Mexican Academy of Logic (AML) Logic Prize 2021’. INCONSISTENCY* IGNORANCE * PARACONSISTENCY [Preprint] [Paper] [9] “Is there anything special about the ignorance involved in Big Data practices?”, in Lundgren, B. L.. and N. Nuñez-Hernández (Eds.) Philosophy of Computing, Philosophical Studies Series, Vol. 143. Forthcoming. IGNORANCE * DEFECTIVE DATA * SC UNDERSTANDING * BIG DATA [Preprint] [Paper] [8] "Is Christ really contradictory? Some methodological concerns from the philosophy of science" in Manuscrito, 2021. Open access. INCONSISTENCY * IGNORANCE [Paper] [7] "The ignorance behind inconsistency toleration" in S.I. Knowing the Unknown Synthese. 2020. IGNORANCE * INCONSISTENCY [Paper] [Preprint] [6] "Inconsistency toleration in the social sciences: Contradictions between theory and observation in economics" (in Spanish) (first author | joint with Josafat Iván Hernández-Cervantes) in Perspectiva Filosofica (47) 2. 2020. Open access. INCONSISTENCY [Paper] [5] “Are you a selective-realist dialetheist without knowing it?” Revista Colombiana de Filosofía de la Ciencia 19(38). 2019. Open access. SC REALISM * INCONSISTENCY * HPS [Paper] [4] “Keeping Globally Inconsistent Scientific Theories Locally Consistent” (joint with Michéle Friend) In: Carnielli W., Malinowski J. (eds) Contradictions, from Consistency to Inconsistency. Trends in Logic (Studia Logica Library), vol 47. Springer; pp 53-88, 2018. DEFECTIVE DATA * INCONSISTENCY [Paper] [3] “The possibility and fruitfulness of a debate on the principle of non-contradiction” (second author | Joint with Luis Estrada- González) In: Carnielli W., Malinowski J. (eds) Contradictions, from Consistency to Inconsistency. Trends in Logic (Studia Logica Library), vol 47. Springer; pp 33-51, 2018. INCONSISTENCY * HISTORY OF LOGIC [Paper] [2] “May the Reinforcement Be with You: On the Reconstruction of Scientific Episodes” (first author| Joint with Luis Estrada-González) Journal of the Philosophy of History 12 (2):259–283 (2018) HPS * DEFECTIVE DATA * INCONSISTENCY [Paper] [Preprint] [1] “Holism, Inconsistency Toleration and Inconsistencies between Theory and Observation” Humana Mente Journal of Philosophical Studies 32:117-147, 2017. Open access. IGNORANCE * INCONSISTENCY [Paper]
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EDITED COLLECTIONsIN ENGLISH
[Under contract] From Contradiction to Defectiveness to Pluralism in Science: Philosophical and Formal Analyses (with Otávio Bueno) -Synthese Library. Studies in Epistemology, Logic, Methodology, and Philosophy of Science. [1] Beyond Toleration? Inconsistency and Pluralism in the Empirical Sciences (with Luis Estrada-González) Special issue of Humana.Mente Journal of Philosophical Studies, Issue 32 - August 2017. IN SPANISH [Under contract] S.I. Visiones estructuralistas sobre la ciencia: Reflexiones en torno a la obra de Adolfo García de la Sienra Guajardo (with Alejandro Vázquez del Mercado Hernandez) Special issue of Revista Stoa. [Forthcoming] Perspectivas y horizontes de la filosofía de la ciencia (with Blanca M. Cárdenas Carrión) Facultad de Ciencias, UNAM. PUBLIC ENGAGEMENT
[3] Interview with Tomasz Jarmuzek
The Reasoner, 16(1). [2] "Pascal's wager applied to COVID-19: Philosophical reflections about risk" (In Spanish) Joint with Gabrielle Ramos-García Aion.mx, (51). [Most read AionMx-article in 2020] [1] "Interview to Phillip Bricker" joint with Moisés Macías-Bustos The Reasoner, 14 (1).
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I have worked mainly in
Inconsistency in science
since 2014
since 2014
My research aims at providing philosophical understanding of the phenomenon of inconsistency toleration in empirical sciences, specifically the toleration of inconsistencies between theory and observation.
In order to do so, my research has focussed on different facets of the phenomenon of inconsistency toleration in the empirical sciences, some of which include:
In order to do so, my research has focussed on different facets of the phenomenon of inconsistency toleration in the empirical sciences, some of which include:
- The epistemological side: In particular, I have studied the role of ignorance when explaining the rational toleration of contradictions in the sciences.
- The formal side: I have addressed the question: how can certain paraconsistent formal tools account for cases of inconsistency toleration in empirical sciences. In order to answer to such question, I have provided a detailed analysis of three cases on inconsistencies from the empirical sciences, and I confront such cases with three paraconsistent formal tools, namely, Chunk and Permeate, Partial Structures and Adaptive Logics.
- The historical side: I have researched in detail four historical episodes that illustrate the toleration of contradictions between theory and observation.
(PHILOSOPHICAL) UNDERSTANDING + HPS
SINCE 2017
SINCE 2017
I’m primarily concerned with the possibility of achieving philosophical understanding in the philosophy of science --even if using defective (historical) information to support philosophical theses. I have focussed on the question What could be the value of historically inaccurate reconstructions for the philosophy of science? I have argued that philosophically-biased reconstructions, even if not historically accurate, can play a highly important epistemic role for the development of the philosophy of science, namely, to enhance our understanding of philosophical theses about science.
UNDERSTANDING DEFECTIVE INFORMATION IN SCIENCE AND PHILOSOPHY
since 2019
since 2019
It is undeniable that scientific understanding is a fundamental component of any successful scientific enterprise; understanding a theory allows scientists to find new domains of application for it, and understanding an empirical domain makes it possible to build new theoretical approaches to that domain. Unfortunately, and despite the value of scientific understanding for the development of science, it is a phenomenon that still remains largely unexplored in the philosophical literature.
In particular, while much current scientific practice makes use of defective (partial, vague, conflictive, inconsistent, and false) information (cf. Arenhart, J. R. B. and Krause 2016; Bueno 1997, 1999, 2006, 2011, 2017, da Costa 2000; da Costa and French 2002, 2003; da Costa and Krause 2014; Priest 2002) philosophers of science have struggled to explain how, if possible, scientists can achieve understanding when using this type of information.
In this respect two main stories have been told. On the one hand, there have been those who characterize understanding as an epistemic achievement that comes only after having obtained explanatory knowledge; this type of understanding has received the name of explanatory understanding (cf. Kvanvig 2003; Grimm 2006, 2014; Morris 2012; Strevens 2013, 2017; Kelp 2014; Sliwa 2015; Lawler 2016, 2018). If understanding is essentially explanatory, it would be available only if the content of the scientist’s beliefs is true, and it would be impossible to achieve understanding via the use of defective (partial, vague, conflictive, inconsistent, and false) information. On the other hand, if scientific understanding is non-explanatory, it could be achieved through the use of defective information; and, although, according to this view, cases of explanatory understanding would be legitimate cases of understanding, they would not by so in virtue of the satisfaction of the factual condition of knowledge or the previous acquisition of causal knowledge (Pettit, 2002; Elgin 2004, 2007, 2017; De Regt y Dieks 2005; De Regt 2009, 2015; Khalifa 2013; De Regt and Gijsbers 2017; Le Bihan 2017, Wilkenfeld 2017; Wilkenfeld, Plunkett, and Lombrozo 2018).
My working hypothesis is that scientific understanding is an extremely complex phenomenon that encompasses a range of types of understanding that include explanatory understanding (under some circumstances) as well as non-explanatory understanding (under different circumstances).
Through my research, I will propose a model of scientific understanding that recognizes different types and degrees of understanding, some of which, I argue, are achievable through the use of defective information. In parallel, I will seek to extend the results of this research to cases of philosophy of science; this will shed light on both scientific understanding and philosophical understanding.
I will explore the possibility of relating different types of defects (partiality, vagueness, conflict, inconsistency and falsehood) to different degrees and types of understanding. The novelty of such an exploration would be that, even if non-explanatory understanding has been strongly advocated by epistemologists of science, the view still lacks a fine-grained analysis of the different ways in which understanding is available for the epistemic agents although the necessary conditions for explanation remain unsatisfied. My proposal consists in providing such a more fine-grained analysis.
In particular, while much current scientific practice makes use of defective (partial, vague, conflictive, inconsistent, and false) information (cf. Arenhart, J. R. B. and Krause 2016; Bueno 1997, 1999, 2006, 2011, 2017, da Costa 2000; da Costa and French 2002, 2003; da Costa and Krause 2014; Priest 2002) philosophers of science have struggled to explain how, if possible, scientists can achieve understanding when using this type of information.
In this respect two main stories have been told. On the one hand, there have been those who characterize understanding as an epistemic achievement that comes only after having obtained explanatory knowledge; this type of understanding has received the name of explanatory understanding (cf. Kvanvig 2003; Grimm 2006, 2014; Morris 2012; Strevens 2013, 2017; Kelp 2014; Sliwa 2015; Lawler 2016, 2018). If understanding is essentially explanatory, it would be available only if the content of the scientist’s beliefs is true, and it would be impossible to achieve understanding via the use of defective (partial, vague, conflictive, inconsistent, and false) information. On the other hand, if scientific understanding is non-explanatory, it could be achieved through the use of defective information; and, although, according to this view, cases of explanatory understanding would be legitimate cases of understanding, they would not by so in virtue of the satisfaction of the factual condition of knowledge or the previous acquisition of causal knowledge (Pettit, 2002; Elgin 2004, 2007, 2017; De Regt y Dieks 2005; De Regt 2009, 2015; Khalifa 2013; De Regt and Gijsbers 2017; Le Bihan 2017, Wilkenfeld 2017; Wilkenfeld, Plunkett, and Lombrozo 2018).
My working hypothesis is that scientific understanding is an extremely complex phenomenon that encompasses a range of types of understanding that include explanatory understanding (under some circumstances) as well as non-explanatory understanding (under different circumstances).
Through my research, I will propose a model of scientific understanding that recognizes different types and degrees of understanding, some of which, I argue, are achievable through the use of defective information. In parallel, I will seek to extend the results of this research to cases of philosophy of science; this will shed light on both scientific understanding and philosophical understanding.
I will explore the possibility of relating different types of defects (partiality, vagueness, conflict, inconsistency and falsehood) to different degrees and types of understanding. The novelty of such an exploration would be that, even if non-explanatory understanding has been strongly advocated by epistemologists of science, the view still lacks a fine-grained analysis of the different ways in which understanding is available for the epistemic agents although the necessary conditions for explanation remain unsatisfied. My proposal consists in providing such a more fine-grained analysis.