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This has been called the problem of Bayes-compatibility for pooling functions. It is known that in a common prior setting, under standard assumptions, linear pooling cannot be nontrivially Bayes-compatible. We show by contrast that geometric pooling can be nontrivially Bayes-compatible. Indeed, we show that, under certain assumptions, geometric and Bayes-compatible pooling are equivalent. Granting supra-Bayesianism its usual normative status, one upshot of our study is thus that, in a certain class of epistemic contexts, geometric pooling enjoys a normative advantage over linear pooling as a social learning mechanism. We discuss the philosophical ramifications of this advantage, which we show to be robust to variations in our statement of the Bayes-compatibility problem.<\/jats:p>","DOI":"10.1017\/s1755020320000416","type":"journal-article","created":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T04:52:32Z","timestamp":1603255952000},"page":"298-337","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":9,"title":["SUPPORT FOR GEOMETRIC POOLING"],"prefix":"10.1017","volume":"16","author":[{"given":"JEAN","family":"BACCELLI","sequence":"first","affiliation":[]},{"given":"RUSH T.","family":"STEWART","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2020,10,21]]},"reference":[{"key":"S1755020320000416_r26","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1177013825"},{"key":"S1755020320000416_r4","doi-asserted-by":"publisher","DOI":"10.1007\/s11238-017-9639-3"},{"key":"S1755020320000416_r3","unstructured":"Bonanno, G. , & Nehring, K. 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