Towards a Conceptual Framework for Conspiracy Theory Theories

ABSTRACT

I present a conceptual framework for classifying generalist and particularist approaches to conspiracy theories (CTs). Specifically, I exploit a probabilistic version of the hexagon of opposition which allows for systematically visualising the logical relations among basic philosophical positions concerning CTs. The probabilistic interpretation can also account for positions, which make weaker claims about CTs: e.g. instead of claiming ‘every CT is suspicious’ some theorists might prefer to claim ‘most CTs are suspicious’ and then ask about logical consequences of such claims. Finally, I illustrate the proposed conceptual framework by selected claims about CTs drawn from the CT research literature.

Video abstract

KEYWORDS:

• Conspiracy theory research
• conceptual framework
• logical relations
• particularism versus generalism, probabilistic hexagon of opposition

Acknowledgments

I am indebted to M R. X. Dentith who pointed me to relevant literature, as well as Matthew Shields, for helpful reviews. Thanks also to the participants of Hans Rott’s seminar ‘New work in theoretical philosophy’ (Department of Philosophy, University of Regensburg, summer semester 2022) for useful comments on an earlier draft of this paper.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. See the first article by M R. X. Dentith (forthcoming a) in this special issue for coverage of what generalism and particularism are.

2. For a gentle introduction to probability logic see Pfeifer (2021) and for more technical details see, e.g. Coletti and Scozzafava (2002) and Hailperin (1999).

3. Of course claims about CT events can be analysed from different levels of abstraction. The Caesar example is an instance of high abstraction. As pointed out by Keeley (1999), however, CTs make claims about many events, like the particular episodes leading to the assassination of Cesar. CTs also contain claims about errant data (Keeley 1999) like events not explained by the received view or events which actually contradict claims made within the received view. Still, I argue, an important class of these events (of whatever level of abstraction) are single case events, which occur only once at a certain time and place. The probabilistic interpretation I propose to use for the analysis of CTs is able to treat both, single case-events and types or classes of (replicable) events.

4. Under frequency-based semantics, e.g. Peters and Westerståhl argue in a similar vein: ‘How many Ss must be P in order for Most Ss are P to be true? Sometimes any number more than half seems enough, but other times a larger percentage is required’ (Peters and Westerståhl 2006, 44, fn. 33).

5. Harris (2018, 250) claims that ‘modus tollens does not have a parallel legitimate probabilistic counterpart’ like modus ponens. Let me correct this statement. Like modus ponens, modus tollens has a probabilistic counterpart: the premise probabilities of modus tollens (e.g. p(¬E₂) = 1 and p(E₂ |E₁) = 1) constrain its conclusion probability (in this case: p(¬E₁) = 1). Maybe Harris had contraposition in mind, since its unrestricted form is probabilistically non-informative: for any p(E₂ |E₁), this premise implies only the (non-informative) unit interval for the conclusion p(¬E₁ | ¬E₂); i.e. even in the extreme case when p(E₂ |E₁) = 1, only 0 ≤ p(¬E₁ | ¬E₂) ≤ 1 can be inferred. Hence contraposition is probabilistically invalid while modus tollens is indeed probabilistically valid (see, e.g. Pfeifer and Kleiter 2009; Table 2, and Pfeifer 2014, 854, for common confusions between modus tollens and contraposition).

6. Thanks to Matthew Shields, who pointed me to the fact that Cassam abandoned his 2016 generalist view – that beliefs in conspiracy theories are the result of intellectual vice – in favour of his 2019 version of generalism, where he now claims that conspiracy theories are forms of political propaganda and therefore have various epistemic flaws.

7. See Dentith’s other article in this same special issue for a similar argument (forthcoming b).

Additional information

Funding

This work was supported by the BMBF research project [01UL1906X].

Notes on contributors

Niki Pfeifer

Niki Pfeifer was awarded his first PhD in psychology (with distinction) at the University of Salzburg (Austria, 2006) and his second PhD in philosophy (with distinction) at the Tilburg Center for Logic and Philosophy of Science (The Netherlands, 2012). After his postdoc years at the Department of Psychology at the University of Salzburg, he moved to the Munich Center of Mathematical Philosophy (LMU Munich, Germany) in 2010, where he worked until 2018. He currently works at the Department of Philosophy of the University of Regensburg (Germany), where he has been teaching philosophy since 2015.