In this paper, we will put some timely network approaches, used in "cultural evolutionary theory" (CET) to the test, comparing their specific explanatory power. CET applies Darwinian principles to understand how traits like language, technology and norms spread, mutate, and persist. We evaluate four CET network models: (a) Phylogenetic Trees, (b) Death-Birth Networks, (c) Interaction Graphs and (c) Trait Networks. (a) excel at modeling vertical transmission but struggle with horizontal exchange. (b) reveal feedback between network structure and trait evolution but oversimplify edge dynamics (c) capture dynamic trait transmission but are often quite complicated. (d) effectively model co-evolving traits but neglect social agents.

We then evaluate these different models against the background of four classical philosophy of science explanations: Causal-Mechanical, Statistical Relevance, Unificationist and Pragmatic explanations. Each model has strengths and weaknesses concerning each kind of explanation. This comparative analysis illuminates which approaches best explain different aspects of CET.

In models of natural selection, fitness is often defined as an organism’s number of descendants. Due to stochastic factors, this number is commonly treated as a random variable. Proponents of the Propensity Interpretation of Fitness (PIF) acknowledge this by defining fitness as a token organism’s propensity to leave descendants. However, as Sober (2022) has argued, such single-case propensities are epistemically inaccessible: we cannot reliably estimate them when each organism provides only one “trial.” While some authors suggest that cloning experiments might help secure the epistemic accessibility of token fitnesses, Eagle (2004) has shown that experimentally generated frequencies alone cannot pin down single-case propensities, as different propensity assignments can be compatible with the same frequencies.

In response, this talk proposes a “long-run” propensity interpretation of fitness, defining fitness as the propensity of organism types to produce a certain number of descendants in the long run, with a specific limiting frequency. With suitable inductive uniformity assumptions, this approach allows empirical testing of fitness-value hypotheses through their inductive consequences for finite frequencies. By showing how to apply fitness measures so construed to prima facie problematic cases such as cyclic or chaotic evolutionary dynamics, I defend this approach against various objections in the literature.

Democratic theorists and social epistemologists often celebrate the epistemic benefits of diversity. One of the cornerstones is the ‘diversity trumps ability’ theorem and simulation results by Hong and Page (2004). Ironically, the interplay between diversity and ability is rarely studied in radically different frameworks. In fact, Hong and Page’s landscape models apply predominantly to decision problems where the groups must find the optimal decision among thousands of options. Their landscape models are ineffective in binary and sparse decision problems (i.e., involving a few options). To fill this gap, I will introduce a new source reliability framework for binary decision problems, where agents rely on imperfect sources to identify the best solution. I use this new source reliability framework to assess whether, when, and (if so) why diversity trumps expertise in binary decision problems

An aspect of the indigenous struggle against colonial oppression is the struggle for the inclusion of their knowledge in policymaking. Perceived as epistemically inferior to science, indigenous knowledge and thus interests are systematically excluded in science-based policy. This article advances an anti-colonial political philosophy of science. As indigenous knowledge feeds into the necessary political value judgements in policy-relevant science, indigenous knowledge inclusion, I contend, should be treated as a political, not solely epistemic, matter. I further argue that indigenous peoples, not just scientists, should have the power to make such political value judgements given the politics of representation under coloniality.