We identify a species of experiment—Kon-Tiki experiments—used to demonstrate the competence of a cause to produce a certain effect, and we examine their role in the historical sciences. We argue that Kon-Tiki experiments are used to test middle-range theory, to test assumptions within historical narratives, and to open new avenues of inquiry. We show how the results of Kon-Tiki experiments are involved in projective inferences, and we argue that reliance on projective inferences does not provide historical scientists with any special (...) protection against the problem of unconceived alternatives. (shrink)

V nasledujúcom príspevku sa snažíme zdôvodniť vyčlenenie troch typov procesov v pozorovanom vesmíre - procesov slabo, stredne a silne usmernených, a to na základe rôznej miery autonómnosti ich štruktúrnych prvkov a rôznej miery či intenzity zákonov, ktorými sú usmerňované alebo riadené. Individuálne a konkrétne procesy sú tak v podstate totožné s individuálnymi a konkrétnymi systémami, cez ktoré, v ktorých a prostredníctvom ktorých sa úplne realizujú, disponujúc tak vždy a všade vlastným substanciálnym obsahom. Na tomto základe potom vyčleňujeme slabo usmernené procesy (...) v neživej prírode s málo vyčlenenými alebo autonómnymi štruktúrnymi prvkami, stredne usmernené procesy živej prírody s oveľa väčšími, vyčlenenejšími a autonómnejšími štruktúrnymi prvkami vo forme živých buniek a postupne rastúcich a zdokonaľujúcich sa organizmov a tried organizmov a nakoniec silne usmernené procesy tzv. sociálnej prírody alebo ľudskej spoločnosti, pozostávajúcej z ľudí ako svojich základných alebo štruktúrnych prvkov a tiež z nimi generovaného technického a/lebo civilizačného "obalu", ktoré sú podobne ako živé procesy a systémy usmerňované a riadené čoraz väčším počtom pre nich špecifických vedeckých zákonov, princípov alebo "pravidiel". (shrink)

Philosophers have usually highlighted how the weakness and paucity of historical evidence underdetermine the choice between rival historical explanations. Focusing underdetermination on the link between theory and evidence comes, I argue, with three assumptions: competing hypotheses are easy to generate, investigators agree on the constitution and interpretation of the evidence and a plurality of hypotheses is a useful evil to reach consensus. The last assumption implies that the sustained coexistence of incompatible hypotheses is considered as a scientific failure. I argue (...) that this negative vision of sustained disagreement has monistic undertones. By drawing from a case study in evolutionary biology, this paper defends a form of scientific pluralism. Firstly, I show that underdetermination is not only found at the inferential level but also at the level of the constitution and interpretation of the evidence, on the choice of investigative scaffolds and when interpreting background theories. Because of that, competing hypotheses exhibit a degree of methodological incommensurability. While catastrophic from a monistic standpoint, I defend that scientific pluralism gives a different, and I think richer, account of such situations. On the plus side, competing approaches benefit from their sustained coexistence and interaction. I argue that this generates direct and indirect epistemic goods independently of whether the controversy is solved. Scientific pluralism also shifts our attention from achieving consensus to managing disagreement. The challenge becomes to maintain the conditions for fruitful interactions in a community with incommensurable approaches and heterogeneous expertise. (shrink)

Philosophers have yet to provide a systematic analysis of the relationship between historical science and model-based science. In this paper I argue that prototypical model-based sciences exhibit features understood to be central to historical science. Philosophers of science have argued that historical scientists are distinctly concerned with inference to the best explanation, that explanations in historical science tend to increase in complexity over time, and that the explanations take the form of narratives. Using general circulation models in climate science as (...) a reference, I illustrate how simulation models in model-based science share these features exhibited by historical science. That model based sciences share these features raises important philosophical questions about how we should understand prototypical types of scientific enquiry, including the relationship between experimental science, historical science, and model-based science. I conclude by exploring several options for how to accommodate the noted similarities within a more general taxonomy of the sciences. (shrink)

Three competing ‘methods’ have been endorsed for inferring phylogenetic hypotheses: parsimony, likelihood, and Bayesianism. The latter two have been claimed superior because they take into account rates of sequence substitution. Can rates of substitution be justified on its own accord in inferences of explanatory hypotheses? Answering this question requires addressing four issues: (1) the aim of scientific inquiry, (2) the nature of why-questions, (3) explanatory hypotheses as answers to why-questions, and (4) acknowledging that neither parsimony, likelihood, nor Bayesianism are inferential (...) actions leading to explanatory hypotheses. The aim of scientific inquiry is to acquire causal understanding of effects. Observation statements of organismal characters lead to implicit or explicit why-questions. Those questions, conveyed in data matrices, assume the truth of observation statements, which is contrary to subsequently invoking substitution rates within inferences to phylogenetic hypotheses. Inferences of explanatory hypotheses are abductive in form, such that some version of an evolutionary theory(ies) is/are included or implied. If rates of sequence evolution are to be considered, it must be done prior to, rather than within abduction, which requires renaming those putatively-shared nucleotides subject to substitution rates. There are, however, no epistemic grounds for renaming characters to accommodate rates, calling into question the legitimacy of causally accounting for sequence data. (shrink)