Business models for biomedical research prescribe decentralization due to market selection pressures. I argue that decentralized biomedical research does not match four normative philosophical models of the role of values in science. Non-epistemic values affect the internal stages of for-profit biomedical science. Publication planning, effected by Contract Research Organizations, inhibits mechanisms for transformative criticism. The structure of contracted research precludes attribution of responsibility for foreseeable harm resulting from methodological choices. The effectiveness of business strategies leads to overrepresentation of profit values (...) versus the values of the general public. These disconnects in respect to the proper role of values in science results from structural issues ultimately linked to the distinct goals of business versus applied science, and so it seems likely that disconnects will also be found in other dimensions of attempts to combine business and science. The volume and integration in the publishing community of decentralized biomedical research imply that the entire community of biomedical research science cannot match the normative criteria of community-focused models of values in science. Several proposals for changing research funding structure might successfully relieve market pressures that drive decentralization. (shrink)

I’m grateful to Aleta Quinn and Studies in History and Philosophy of Science for hosting this book forum for my book, The Relativity of Theory (Springer, 2020). I’m also grateful to Margaret Greta Turnbull and Joseph Martin for their commentaries. In what follows, I address their comments as I understand them.

This dissertation is centrally concerned with exploring obituaries as repositories of values. Obituaries are a publicly-available natural language source that are variably written for members of communities that are wide (nation- level) and narrow (city-level, or at the level of specific groups therein). Because they are explicitly summative, limited in size, and written for consumption by a public audience, obituaries may be expected to express concisely the aspects of their subjects’ lives that the authors (often family members living in the (...) same communities) found most salient or worthy of featuring. 140,599 obituaries nested in 832 newspapers from across the USA were scraped with permission from Legacy.com, an obituaries publisher. Obituaries were coded for the age at death and gender (female/male) of the deceased using automated algorithms. For each publishing newspaper, county-level median income, educational achievement (operationalized as percent of the population with a Bachelor’s degree or higher), and race and ethnicity were averaged across counties, weighting by population size. A Neo4J graph database was constructed using WordNet and the University of South Florida Free Association Norms datasets. Each word in each obituary inthe corpus was lemmatized. The shortest path through the WordNet graph from each lemma to 30 Schwartz value prototype words published by Bardi, Calogero, and Mullen (2008) was then recorded. From these path lengths, a new measure, “word-by-hop,” was calculated for each Schwartz value to reflect the relative lexical distance between each obituary and that Schwartz value. Of the Schwartz values, Power, Conformity, and Security were most indicated in the corpus, while Universalism, Hedonism, and Stimulation were least indicated. A series of seven two-level regression models suggested that, across Schwartz values, newspaper community accounted for the greatest amount of word-by-hop variability in the corpus. The best-fitting model indicated a small, negative effect of female status across Schwartz values. Unexpectedly, Hedonism and Conformity, which had conceptually opposite prototype words, were highly correlated, possibly indicating that obituary authors “compensate” for describing the deceased in a hedonistic way by concurrently emphasizing restraint. Future research could usefully further expand word-by-hop and incorporate individual-level covariates that match the newspaper-level covariates used here. (shrink)