On the Evidential Import of Unification. Myrvold, W. C. Philosophy of Science, 84(1):92–114, August, 2016.
On the Evidential Import of Unification [link]Paper  doi  abstract   bibtex   
There are two senses in which a hypothesis may be said to unify evidence: (1) ability to increase the mutual information of a set of evidence statements; (2) explanation of commonalities in phenomena by positing a common origin. On Bayesian updating, only Mutual Information Unification contributes to incremental support. Defenders of explanation as a confirmatory virtue that makes independent contribution must appeal to some relevant difference between humans and Bayesian agents. I argue that common origin unification has at best a limited heuristic role in confirmation. Finally, Reichenbachian common cause hypotheses are shown to be instances of Mutual Information Unification.
@article{myrvold_evidential_2016,
	title = {On the {Evidential} {Import} of {Unification}},
	volume = {84},
	issn = {0031-8248},
	url = {http://www.journals.uchicago.edu.proxy.library.nd.edu/doi/full/10.1086/688937},
	doi = {10.1086/688937},
	abstract = {There are two senses in which a hypothesis may be said to unify evidence: (1) ability to increase the mutual information of a set of evidence statements; (2) explanation of commonalities in phenomena by positing a common origin. On Bayesian updating, only Mutual Information Unification contributes to incremental support. Defenders of explanation as a confirmatory virtue that makes independent contribution must appeal to some relevant difference between humans and Bayesian agents. I argue that common origin unification has at best a limited heuristic role in confirmation. Finally, Reichenbachian common cause hypotheses are shown to be instances of Mutual Information Unification.},
	number = {1},
	urldate = {2017-05-26},
	journal = {Philosophy of Science},
	author = {Myrvold, Wayne C.},
	month = aug,
	year = {2016},
	keywords = {BAYESIAN analysis, Bayesian analysis, EVIDENCE, Evidence, HYPOTHESIS, Hypothesis, INFORMATION measurement, Information measurement, UNIFICATION grammar, Unification grammar},
	pages = {92--114}
}
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