1,721,335 research outputs found
Commented Bibliography on Models and Idealizations
No full textThis chapter provides a classified and commented bibliography of printedbooks on the philosophy of scientific modeling and related issues, such as representation,idealization, computer simulation, and others. It is intended as a guide forfurther readings concerning the main topics of the preceding chapters.Fil: Cassini, Alejandro Pablo F.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin
Deidealized Models
No full textThis chapter analyzes how highly idealized theoretical models canbe deidealized. He argues that idealized models are built with a definite purpose andfor that reason, the advantages and disadvantages of idealizing depend essentially onthe specific purpose for which a given model is designed. As a consequence, evenwhen deidealization may be feasible, a cost–benefit analysis may suggest avoidingit. He exemplifies those circumstances with a study of deidealized models of theSolar System and physical pendula. He concludes that deidealization has not tobe conceived of as an end in itself, or as aiming at a veridical representation of thephenomena, but rather as ameans to other ends, such as obtaining better explanationsor predictions, or more generally, improving the expediency of our models to solvethe problems that originated their construction.Fil: Cassini, Alejandro Pablo F.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin
Theories, Models, and Scientific Representations
No full textAlejandro Cassini and Juan Redmond offer an elementary but fairly complete and extensive introduction to the present state of the philosophy of scientific models. It was written with the purpose of providing the readers an accessible account of the main topics that have been discussed and elaborated on by the most distinguished philosophers of science in the last two decades. It also provides a brief historical narrative of the rise and the early development of the philosophy on scientific models since the middle of the twentieth century.Fil: Cassini, Alejandro Pablo F.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: Redmond, Juan José. Universidad de Valparaíso; Chil
Rala is involved in the transformation mechanisms induced by the oncogenes v-Raf, v-Raf, v-Src
No full textFil: Adam, Alejandro Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Ciencia y seudociencia: ¿por qué todavía es importante distinguirlas?
Get PDF¿Cómo se distingue la ciencia de la seudociencia? ¿Dónde debe trazarse la frontera? El problema dela demarcación está lejos de ser simple y todavía no tiene una solución general satisfactoria. El trabajo analiza diferentes criterios de demarcación y muestra que no resultan necesarios y/o suficientes para distinguir la ciencia de la seudociencia. Concluye que, no obstante, el problema de la demarcación tiene importancia social y educativa, por lo que no es posible prescindir de algún conjunto de criterios, aunque resulten parciales.Fil: Cassini, Alejandro Pablo F.. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Filosofía "Dr. Alejandro Korn"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Un experimento crucial de Galileo sobre la velocidad de la luz
Get PDFUn experimento crucial es uno que se propone decidir entre dos hipótesis o teorías rivales. Galileo, según afirma él mismo, fue el primero en concebir y realizar una experiencia para tratar de determinar si la luz se propaga de manera instantánea o sucesiva, es decir, con una velocidad infinita o finita. El experimento tuvo un resultado negativo, pero, además de señalar el camino para futuras experiencias, nos dejó importantes lecciones de carácter epistemológico.Fil: Cassini, Alejandro Pablo F.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin
Ciencia y seudociencia: ¿por qué todavía es importante distinguirlas?
Get PDF¿Cómo se distingue la ciencia de la seudociencia? ¿Dónde debe trazarse la frontera? El problema dela demarcación está lejos de ser simple y todavía no tiene una solución general satisfactoria. El trabajo analiza diferentes criterios de demarcación y muestra que no resultan necesarios y/o suficientes para distinguir la ciencia de la seudociencia. Concluye que, no obstante, el problema de la demarcación tiene importancia social y educativa, por lo que no es posible prescindir de algún conjunto de criterios, aunque resulten parciales.Fil: Cassini, Alejandro Pablo F.. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Filosofía "Dr. Alejandro Korn"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Simulation models and probabilities: a Bayesian defense of the value-free ideal
No full textSome philosophers of science have recently argued that the epistemic assessment of complex simulation models, such as climate models, cannot be free of the influence of social values. In their view, the assignment of probabilities to the different hypotheses or predictions that result from simulations presupposes some methodological decisions that rest on value judgments. In this article, I criticize this claim and put forward a Bayesian response to the arguments from inductive risk according to which the influence of social values on the calculation of probabilities is negligible. I conclude that the epistemic opacity of complex simulations, such as climate models, does not preclude the application of Bayesian methods.Fil: Cassini, Alejandro Pablo F.. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Filosofía "Dr. Alejandro Korn"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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