LESZEK NOWAK ON SCIENTIFIC LAWS AND SCIENTIFIC EXPLANATION

2007 ◽  
pp. 167-178
Keyword(s):  
Scientific Explanation ◽  
Scientific Laws

scholarly journals La función explicativa de los modelos en biología

2013 ◽  
Author(s):  
Antonio Diéguez
Keyword(s):  
Social Sciences ◽  
Scientific Explanation ◽  
Scientific Explanations ◽  
The Past ◽  
Scientific Laws

RESUMENLos modelos científicos son recursos explicativos fundamentales en la ciencia, y particularmente en aquellas ciencias en las que es dudoso que podamos contar con leyes científicas genuinas, como es el caso de la biología (y de las ciencias sociales). La cuestión de cómo explican los modelos ha despertado una gran atención en las últimas décadas y, sin embargo, sigue siendo una cuestión controvertida. Hay muchos tipos de modelos y no es de extrañar, por tanto, que puedan proporcionar explicaciones de los fenómenos de formas muy diversas. Si se puede señalar un rasgo común a todos estos modos diferentes de explicar, es el hecho de que los modelos nos ofrecen una mejor comprensión de los fenómenos. Se argumenta en este trabajo que la noción de ‘comprensión’ aquí implicada no es irremediablemente subjetiva.PALABRAS CLAVEMODELOS BIOLÓGICOS, EXPLICACIÓN CIENTÍFICA, COMPRENSIÓN, LEYES CIENTÍFICASABSTRACTScientific models are basic explanatory resources in science. This explanatory function is especially relevant in biology and social sciences, where it is doubtful the existence of genuine scientific laws. How models can provide scientific explanations has been a widely debated issue in the past decades, but in spite of this fact it remains as a controversial one. There are many kinds of models in biology, so it is not surprising that they provide scientific explanations of phenomena in very different ways. A possible common feature among this diversity is the fact that models give us a better understanding of phenomena. It is argued in this paper that the notion of ‘understanding’ is not irremediably subjective.KEYWORDSBIOLOGICAL MODELS, SCIENTIFIC EXPLANATION, UNDERSTANDING, SCIENTIFIC LAWS

Magnitudes

2019 ◽  
pp. 39-71
Author(s):  
Christopher Peacocke
Keyword(s):  
Scientific Explanation ◽  
Perceptual Content ◽  
Seven Principles ◽  
Analogue Computation ◽  
Scientific Laws

A new realistic account of an ontology of extensive magnitudes is developed, formulated in Seven Principles. The principles are defended by the role of magnitudes in scientific explanation and in counterfactuals. Scientific laws can be formulated using this ontology of magnitudes. A metaphysics-first view of the perception of magnitudes is then defended by using this metaphysics of magnitudes. The metaphysics-first treatment permits explanation of features of the perception of extensive magnitudes. Notions of analogue computation, analogue representation, and analogue content are explained using this apparatus. Deployment of the resulting theory allows the development, against Kuhn, of a case for the objectivity of analogue perceptual content.

C.G. HEMPEL’S PHILOSOPHY: DEDUCTIVE-NOMOLOGICAL MODEL OF HISTORICAL EXPLANATION

2020 ◽  
pp. 13-19
Author(s):  
V.P. Potamskaya ◽  
Keyword(s):  
Explicit Form ◽  
Scientific Explanation ◽  
Historical Explanation ◽  
Scientific Laws

The article is devoted to the deductive-nomological model of explanation, which emphasized the most important aspect of scientific explanation – the connection with scientific laws. It is demonstrated thatthe peculiarity of the historical explanation lies in the fact that general laws are not formulated in an explicit form due to their triviality and obviousness.

The Argument from Design—a Defence

1972 ◽  
Vol 8 (3) ◽  
pp. 193-205 ◽  
Author(s):  
R. G. Swinburne
Keyword(s):  
Temporal Order ◽  
Scientific Explanation ◽  
General Regularity ◽  
States Of Affairs ◽  
Gas Laws ◽  
Intentional Explanation ◽  
Scientific Laws ◽  
Argument From Design ◽  
Almost All ◽  
Recent Attack

Mr Olding's recent attack on my exposition of the argument from design gives me an opportunity to defend the central theses of my original article. My article pointed out that there were arguments from design of two types—those which take as their premisses regularities of copresence (spatial order) and those which take as their premisses regularities of succession (temporal order). I sought to defend an argument of the second type. One merit of such an argument is that there is no doubt about the truth of its premisses. Almost all objects in the world behave in a highly regular way describable by scientific laws. Further, any scientific explanation of such a regularity must invoke some more general regularity. (We explain the gas laws by Newton's laws.) The most general regularities of all are, as such, scientifically inexplicable. The question arises whether there is a possible explanation of another kind which can be provided for them, and whether their occurrence gives any or much support to that explanation. I urged that we do explain some phenomena by explanation of an entirely different kind from the scientific. We explain states of affairs by the action of agents who bring them about intentionally of their own choice. Regularities of succession, as well as other phenomena may be explained in this way. Explanation of this kind I will term intentional explanation. Intentional explanation of some phenomenon E consists in adducing an agent A who brought E about of his own choice and a further end G which, he believed, would be forwarded by the production of E. (When an agent brings about E ‘for its own sake’, E will be the same as G.)

Test Validation Without Measurement

2016 ◽  
Vol 32 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Emilie Lacot ◽  
Mohammad H. Afzali ◽  
Stéphane Vautier
Keyword(s):  
Test Data ◽  
Test Scores ◽  
Scientific Explanation ◽  
Test Validation ◽  
Clinical Tests ◽  
Ethical Perspective ◽  
Power Of Test ◽  
Memory Accuracy ◽  
Social Uses ◽  
Special Case

Abstract. Test validation based on usual statistical analyses is paradoxical, as, from a falsificationist perspective, they do not test that test data are ordinal measurements, and, from the ethical perspective, they do not justify the use of test scores. This paper (i) proposes some basic definitions, where measurement is a special case of scientific explanation; starting from the examples of memory accuracy and suicidality as scored by two widely used clinical tests/questionnaires. Moreover, it shows (ii) how to elicit the logic of the observable test events underlying the test scores, and (iii) how the measurability of the target theoretical quantities – memory accuracy and suicidality – can and should be tested at the respondent scale as opposed to the scale of aggregates of respondents. (iv) Criterion-related validity is revisited to stress that invoking the explanative power of test data should draw attention on counterexamples instead of statistical summarization. (v) Finally, it is argued that the justification of the use of test scores in specific settings should be part of the test validation task, because, as tests specialists, psychologists are responsible for proposing their tests for social uses.

Thomas Reid on Causation and Scientific Explanation

2016 ◽  
Vol 14 (1) ◽  
pp. 51-67 ◽  
Author(s):  
Manuel Barrantes ◽  
Juan M. Durán
Keyword(s):  
Common Sense ◽  
Scientific Explanation ◽  
Thomas Reid ◽  
Contemporary Debate ◽  
The Common

We argue that there is no tension between Reid's description of science and his claim that science is based on the principles of common sense. For Reid, science is rooted in common sense since it is based on the (common sense) idea that fixed laws govern nature. This, however, does not contradict his view that the scientific notions of causation and explanation are fundamentally different from their common sense counterparts. After discussing these points, we dispute with Cobb's ( Cobb 2010 ) and Benbaji's ( Benbaji 2003 ) interpretations of Reid's views on causation and explanation. Finally, we present Reid's views from the perspective of the contemporary debate on scientific explanation.

THE SCIENCE OF JUDICIAL PSYCHOLOGY

2019 ◽  
Vol 12 (2) ◽  
pp. 78-87
Author(s):  
Petru TĂRCHILĂ
Keyword(s):  
Criminal Behavior ◽  
Cultural Context ◽  
Scientific Explanation ◽  
Preventive Measures ◽  
Psychosocial Characteristics ◽  
Legal Norms ◽  
Behavioral Profile ◽  
The Individual ◽  
Determining Factor ◽  
Determinant Factor

Judicial psychology is the science that analyzes and tries to understand the criminal phenomenon in general and its determinant factor in particular, by the complexity of factors that generate it and by the diversity of its forms of manifestation. Although the determining factor of criminal behavior is always subjective being generated by the psychic of the offender, this aspect must be correlated with the context in which it manifests itself: social, economic, cultural context etc. Judicial psychology investigates the behavior of the individual in all its aspects, seeking a scientific explanation of the mechanisms and factors enhancing criminal favors, thus enabling the identification of the preventive measures to be taken to reduce the categories of offenses. It studies the psycho-behavioral profile of the offender, identifying the causes that determined its behavior in order to take preventive measures.The domain of judicial psychology is mainly deviance, conduct that departs from the moral or legal norms that are dominant in a given culture. The object of judicial psychology is the criminal act, correlated with the psychosocial characteristics of the participants in the judicial action (offender, victim, witness, investigator, magistrate, lawyer, civil party, educator, etc.). The science of judicial psychology also analyzes how these characteristics appear and manifest themselves in concrete and special conditions of their interaction in three phases of the criminal act: the pre-criminal phase, the actual criminal phase and the post-criminal phase.

Professional pathology in the production of aluminum in the Kola Arctic

2020 ◽  
pp. 767-767
Author(s):  
S. A. Syurin ◽  
S. A. Gorbanev
Keyword(s):  
Working Conditions ◽  
Occupational Diseases ◽  
Scientific Explanation ◽  
Marked Decrease ◽  
The Arctic ◽  
Aluminium Production ◽  
First Time

In 2007-2017, 22 occupational diseases were diagnosed for the first time in 18 workers engaged in aluminium production in the Arctic. A marked decrease in occupational morbidity in 2010-2017 was found, which was not associated with changes in working conditions and therefore requires an appropriate scientific explanation.

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