Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Robustness in the Life Sciences: Issues in Modeling and Explanation

Thompson, Morgan (2020) Robustness in the Life Sciences: Issues in Modeling and Explanation. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

Download (962kB) | Preview


My dissertation introduces two new accounts of how robustness can be used to identify epistemically trustworthy claims. Through an analysis of research practices in the life sciences, I focus on two main senses of robustness: robust reasoning in knowledge generating inferences and explanatory strategies for phenomena that are themselves robust. First, I provide a new account of robustness analysis (called ‘scope robustness analysis’), in which researchers use empirical knowledge to constrain their search for possible models of the system. Scope robustness analysis is useful for scientific discovery and pursuit whereas current accounts of robustness analysis are useful for confirmation. Second, I provide a new account of how researchers use different methods to produce the same result (a research strategy called ‘triangulation’). My account makes two contributions: I criticize a prominent account of the diversity criterion for methods because it analyzes an inferential strategy (i.e., eliminative inference) distinct from the inferential strategy underlying triangulation (i.e., common cause inductive inferences). My account also better explains how triangulation can fail in practice by assessing points of epistemic risk, which I demonstrate by applying it to implicit attitude research. Finally, I contribute to a debate about another sense of robustness: phenomena that occur regardless of changes in their component parts and activities. I argue that some robust phenomena in network neuroscience are not best explained mechanistically by citing their constituent parts (e.g. individual neurons) and their activities, but rather by appealing to features of the connectivity among brain areas.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Thompson, Morganmot14@pitt.edumot140000-0002-8239-1716
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMachery,
Committee MemberChirimuuta,
Committee MemberDanks,
Committee MemberWoodward,
Committee MemberZollman,
Date: 16 September 2020
Date Type: Publication
Defense Date: 14 April 2020
Approval Date: 16 September 2020
Submission Date: 21 April 2020
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 148
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > History and Philosophy of Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: robustness, scientific modeling, triangulation, explanation
Date Deposited: 16 Sep 2020 15:14
Last Modified: 16 Sep 2022 05:15


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item