Scientific reduction and the synonymy principle of property identity

1981 ◽  
Vol 40 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Michael Tye
Keyword(s):  
Property Identity ◽  
Scientific Reduction

Realization, Powers, and Property Identity

The Monist ◽  
2011 ◽  
Vol 94 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Sydney Shoemaker ◽  
Keyword(s):  
Property Identity

Nomic Essentialism

2020 ◽  
pp. 23-44
Author(s):  
Theodore Sider
Keyword(s):  
Laws Of Nature ◽  
Property Identity ◽  
Nomic Role

According to nomic (or causal, or dispositional) essentialists, the identity of a property is tied up with its nomic role, the role it plays in the laws of nature. Modally speaking this is straightforward: a property could not have obeyed different laws. But postmodally it is unclear what it means, since it is hard to see how to state the fundamental facts without mentioning particular properties. Various ideas are considered and criticized, such as that facts about property instantiations, or property existence, or property identity, are grounded in facts about laws; and that the laws are essential to properties. The latter, it is argued, is insufficiently metaphysically specific to count as an improvement on the modal formulation.

A note on the synonymy principle of property identity

Analysis ◽  
1982 ◽  
Vol 42 (1) ◽  
pp. 52-55 ◽  
Author(s):  
M. Tye
Keyword(s):  
Property Identity

scholarly journals Per una fondazione ontologica della “riduzione consapevole e cooperante”

2015 ◽  
Vol 64 (5) ◽  
Author(s):  
Giampaolo Ghilardi ◽  
Vittoradolfo Tambone
Keyword(s):  
Analytical Model ◽  
Scientific Practice ◽  
Scientific Research ◽  
Scientific Methodology ◽  
Human Knowledge ◽  
Viktor Frankl ◽  
Conditions Of Possibility ◽  
Scientific Reduction ◽  
Clinical Methodology ◽  
Different Levels

Il presente lavoro analizza i presupposti ontologici della metodologia scientifica identificata nella formula “riduzione consapevole e cooperante”. Viene studiata l’idea di essere sottesa alle riduzioni scientifiche, distinguendo tra riduzioni legittime e riduzionismo inadeguato, per valutare all’interno della metodologia clinica la complessità dell’agire scientifico. Si sono quindi ricercate le radici ontologiche della complessità nella scienza, approdando così al realismo dimensionale teorizzato per primo da Viktor Frankl. La rigorizzazione di questo modello analitico ci ha condotti a recuperare il tema filosofico dell’analogia quale strumento importante per la razionalità scientifica, in grado mantenere in tensione feconda tra loro i diversi elementi del discorso epistemologico. Questo percorso si è quindi sviluppato sulle condizioni di possibilità della conoscenza umana, rintracciando nella nozione di “potenzialità futura” il tratto distintivo dell’impresa conoscitiva. Il tema è quindi stato approfondito nei suoi fondamenti ontologici principali, analizzando i concetti di potenzialità e possibilità applicati all’ambito conoscitivo. La fondazione ontologica del modello conoscitivo analizzato viene pertanto trovata in un essere analogico, vale a dire composto su diversi livelli non esauribili concettualmente dall’indagine scientifica, ma neppure estranei alla capacità d’indagine umana. ---------- The present work develops the ontological presuppositions of scientific methodology labeled as “aware and cooperative reduction”. The idea of being underlying scientific reduction is analyzed by distinguishing among legitimate and improper reductionism. This framework is useful to assess within the context of clinical methodology the complexity of scientific practice. We also focus on the ontological roots of complexity in science, reaching to what Viktor Frankl has named “dimensional realism”. Thanks to this analytical model we recovered the theme of analogy as an important instrument of scientific rationality, which allows to keep together both the objective and the subjective instances of the epistemological domain. This speculative path lead us to ask about the conditions of possibility of human knowledge. In so doing, we have found the notion of “future potentiality” to be the mark of human knowledge. The result of our inquiry is that “analogical being” is the ontological foundation of scientific methodology. The ontological idea of “analogy” conveys an understanding of being constituted by different levels, or dimensions, which are not conceptually exhaustible within scientific research, but which are nevertheless accessible by human investigation.

scholarly journals Coherence and Reduction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Andrea Giuseppe Ragno
Keyword(s):  
Statistical Mechanics ◽  
Confirmation Theory ◽  
Bayesian Confirmation Theory ◽  
Numerical Examples ◽  
Bayesian Confirmation ◽  
Degree Of Coherence ◽  
Confirmation Measures ◽  
Before And After ◽  
Important Field ◽  
Scientific Reduction

Abstract Synchronic intertheoretic reductions are an important field of research in science. Arguably, the best model able to represent the main relations occurring in this kind of scientific reduction is the Nagelian account of reduction, a model further developed by Schaffner and nowadays known as the generalized version of the Nagel–Schaffner model (GNS). In their article (2010), Dizadji-Bahmani, Frigg, and Hartmann (DFH) specified the two main desiderata of a reduction á la GNS: confirmation and coherence. DFH first and, more rigorously, Tešic (2017) later analyse the confirmatory relation between the reducing and the reduced theory in terms of Bayesian confirmation theory. The purpose of this article is to analyse and compare the degree of coherence between the two theories involved in the GNS before and after the reduction. For this reason, in the first section, I will be looking at the reduction of thermodynamics to statistical mechanics and use it as an example to describe the GNS. In the second section, I will introduce three coherence measures which will then be employed in the comparison. Finally, in the last two sections, I will compare the degrees of coherence between the reducing and the reduced theory before and after the reduction and use a few numerical examples to understand the relation between coherence and confirmation measures.

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