The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Explanatory Unification
Abstract
The official model of explanation proposed by the logical empiricists, the covering law model, is subject to familiar objections. The goal of the present paper is to explore an unofficial view of explanation which logical empiricists have sometimes suggested, the view of explanation as unification. I try to show that this view can be developed so as to provide insight into major episodes in the history of science, and that it can overcome some of the most serious difficulties besetting the covering law model.
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Citations
Cites
Explanation and Scientific Understanding
Friedman, M. (1974) · The Journal of Philosophy · doi:10.2307/2024924 · Cited by 1,386 · cited 1×
“Hence we can endorse something close to Friedman's view of the merits of explanatory unification (Friedman 1974, pp. 18-19).”
Method
Cited by
Salmon, W. C. (1998) · doi:10.1093/0195108647.001.0001 · Cited by 499
Laws for Metaphysical Explanation
Schaffer, J. (2017) · Philosophical Issues · doi:10.1111/phis.12111 · Cited by 133
Explanatory profiles of models of consciousness - towards a systematic classification
Signorelli, C. M., Szczotka, J., & Prentner, R. (2021) · Neuroscience of Consciousness · doi:10.1093/nc/niab021 · Cited by 91
Nomothetic Explanation and Humeanism about Laws of Nature
Bhogal, H. (2020) · Oxford Studies in Metaphysics Volume 12 · doi:10.1093/oso/9780192893314.003.0006 · Cited by 74
Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare
Durán, J. M. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103498 · Cited by 62
Life and Understanding: The Origins of “Understanding” in Self-Organizing Nervous Systems
Yufik, Y. M., & Friston, K. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2016.00098 · Cited by 53
Scientific explanation: A critical survey
Schurz, G. (1995) · Foundations of Science · doi:10.1007/bf00145406 · Cited by 27
Nomological Deductive Reasoning for Trustworthy, Human-Readable, and Actionable AI Outputs
Hakizimana, G., & Ledezma Espino, A. (2025) · Algorithms · doi:10.3390/a18060306 · Cited by 2
Metadata
- Authors
- Kitcher, P.
- Venue
- Philosophy of Science
- Publisher
- Cambridge University Press (CUP)
- Published
- 1981-12
- Volume
- 48
- Issue
- 4
- Pages
- 507-531
- ISSN
- 0031-8248 (ISSN-L)
- 1539-767X
- OpenAlex
- W4244761346
- Cited by
- 1,129
- References
- 1
- FWCI
- 8.87
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
