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Cited by 276

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Understanding Space-Time: The Philosophical Development of Physics from Newton to Einstein

DiSalle, Robert·2006·Cambridge University Press eBooks

Abstract

Presenting the history of space-time physics, from Newton to Einstein, as a philosophical development DiSalle reflects our increasing understanding of the connections between ideas of space and time and our physical knowledge. He suggests that philosophy's greatest impact on physics has come about, less by the influence of philosophical hypotheses, than by the philosophical analysis of concepts of space, time and motion, and the roles they play in our assumptions about physical objects and physical measurements. This way of thinking leads to interpretations of the work of Newton and Einstein and the connections between them. It also offers ways of looking at old questions about a priori knowledge, the physical interpretation of mathematics, and the nature of conceptual change. Understanding Space-Time will interest readers in philosophy, history and philosophy of science, and physics, as well as readers interested in the relations between physics and philosophy.

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Crossref · 10.1017/cbo9780511487361

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Metadata

Authors
DiSalle, R.
Venue
Cambridge University Press eBooks
Published
2006-04-27
OpenAlex
W1548042637
Cited by
276
References
36
FWCI
37.10
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Understanding Space-Time: The Philosophical Development of Physics from Newton to Einstein. https://app.cochat.ai/papers/10.1017/cbo9780511487361
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DiSalle, R. (2006). Understanding Space-Time: The Philosophical Development of Physics from Newton to Einstein. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511487361

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.