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1. Digging deep in the sociality of interaction: lessons from knowledge-making in potato science

   Kendig, Catherine; Bursten, Julia (May 2024, International Society for Philosophy of Science in Practice)

   In her recent "What's Social About Social Epistemology?" (Longino 2022, JFP 109(4)) Helen Longino turns her attention to a particular aspect of the sociality of science, which she terms “the sociality of interaction.” (171) In her account, social interaction among scientific groups is essential to the production of scientific knowledge. She discusses many activities that exemplify the sociality of interaction in the sciences — from the uses of testimony and shared categories for representing phenomena to collecting, sharing, and disagreeing about data — and argues that these activities produce scientific knowledge through social interaction. We are broadly sympathetic to this view. However, in her analysis, Longino argues that “concern with practices that are productive of knowledge, rather than with the content and subject of knowledge” should be the focus. (173, emphasis added) This suggests that it is both possible and desirable to analyze practices without analyzing the content and subject of knowledge, and further that analysis of content-knowledge in a given scientific domain should not be the focus of attention if the goal of a philosophical investigation is understanding scientific knowledge production. We disagree. Consider the agricultural-scientific practice of extension, a type of knowledge-producing work in agricultural science. Extension is a legally and institutionally defined social system that produces interactions between scientists and the public in contemporary U.S. agricultural science. The success conditions of producing extension knowledge are inherently, deeply, and interactively social. In this talk, we show that the sociality of successful knowledge production in extension is inextricable from the “content and subject” of new scientific knowledge produced through extension. We illustrate our point through a discussion of agricultural-scientific research on potatoes. Such research is often carried out via extension. We argue that what potatoes are is intertwined with human interaction. The significance of potatoes as a food crop impacts how research on potatoes occurs, from what questions are asked to what scientific practices are able to be carried out to answer those questions. Most field trials on potatoes occur on privately-held farms that partner with researchers, and commercial farm workers rather than principal investigators grow the crops that produce the objects of study. Extension often mediates these partnerships, and from historical and present-day farmers and extension workers to commercial and academic agricultural scientists, networks of interactively social partnerships remain intertwined with the production of potatoes — and knowledge about them. We show how extension generates content-knowledge that is inseparable from the practices productive of that knowledge. Our analysis is ultimately a friendly amendment to Longino’s view. We take seriously the centrality of the sociality of interaction in producing scientific knowledge. We contend that knowledge co-production practices in agricultural science illustrate (1) how knowledge about agricultural experiment is made through social interaction and (2) why such interaction is essential for epistemic content. What we propose is an admittedly strong form of sociality in which sociality is constitutive of knowledge in a way that without it, that which is being discussed ceases to be knowledge if it is not social. 

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2. Epistemic advantage on the margin: A network standpoint Epistemology

   https://doi.org/10.1111/phpr.12895  

   Wu, Jingyi (June 2022, Philosophy and Phenomenological Research)

   Abstract I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding and application of previously discovered network epistemology effects, notably the Zollman effect (Zollman, 2007, 2010). 

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3. Data science transfer pathways from associate's to bachelor's programs

   https://doi.org/10.1162/99608f92.e2720e81  

   Baumer, Benjamin S.; Horton, Nicholas Jon (January 2023, Harvard Data Science Review)

   Meng, X-L (Ed.)

   A substantial fraction of students who complete their college education at a public university in the United States begin their journey at one of the 935 public 2-year colleges. While the number of 4-year colleges offering bachelor’s degrees in data science continues to increase, data science instruction at many 2-year colleges lags behind. A major impediment is the relative paucity of introductory data science courses that serve multiple student audiences and can easily transfer. In addition, the lack of predefined transfer pathways (or articulation agreements) for data science creates a growing disconnect that leaves students who want to study data science at a disadvantage. We describe opportunities and barriers to data science transfer pathways. Five points of curricular friction merit attention: 1) a first course in data science, 2) a second course in data science, 3) a course in scientific computing, data science workflow, and/or reproducible computing, 4) lab sciences, and 5) navigating communication, ethics, and application domain requirements in the context of general education and liberal arts course mappings. We catalog existing transfer pathways, efforts to align curricula across institutions, obstacles to overcome with minimally disruptive solutions, and approaches to foster these pathways. Improvements in these areas are critically important to ensure that a broad and diverse set of students are able to engage and succeed in undergraduate data science programs. 

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4. Dynamical system model predicts when social learners impair collective performance

   https://doi.org/10.1073/pnas.2106292118  

   Yang, Vicky Chuqiao; Galesic, Mirta; McGuinness, Harvey; Harutyunyan, Ani (August 2021, Proceedings of the National Academy of Sciences)

   A key question concerning collective decisions is whether a social system can settle on the best available option when some members learn from others instead of evaluating the options on their own. This question is challenging to study, and previous research has reached mixed conclusions, because collective decision outcomes depend on the insufficiently understood complex system of cognitive strategies, task properties, and social influence processes. This study integrates these complex interactions together in one general yet partially analytically tractable mathematical framework using a dynamical system model. In particular, it investigates how the interplay of the proportion of social learners, the relative merit of options, and the type of conformity response affect collective decision outcomes in a binary choice. The model predicts that, when the proportion of social learners exceeds a critical threshold, a bistable state appears in which the majority can end up favoring either the higher- or lower-merit option, depending on fluctuations and initial conditions. Below this threshold, the high-merit option is chosen by the majority. The critical threshold is determined by the conformity response function and the relative merits of the two options. The study helps reconcile disagreements about the effect of social learners on collective performance and proposes a mathematical framework that can be readily adapted to extensions investigating a wider variety of dynamics. 

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5. Centering and marginalization in introductory university physics classrooms

   https://doi.org/10.3389/feduc.2023.964699  

   Scherr, Rachel E; Hairston, W Tali; McKagan, Sarah B; Miller, Sophie (October 2023, Frontiers in Education)

   IntroductionResearch-based instructional strategies in physics promote active participation in collaborative activities as a primary means for students to construct understanding. Discussions of physics content are also negotiations of social relations. MethodsVideo analysis of small-group collaborative learning activities in introductory physics classrooms at three different universities, using situated learning theory analyses that include a critical consciousness lens. ResultsStudents’ ability to actively participate in sensemaking may be limited by their peripheral or marginalized position. Some people seem to be centered (or marginalized) for reasons other than the strength of their physics reasoning, and some people’s contributions are elevated (or neglected) for reasons other than their scientific merit. DiscussionSome of the behavioral patterns that we observe typify racialized and gendered interactions that are common in broader U.S. society. 

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