Burden of proof (philosophy)
The burden of proof (Latin: onus probandi, shortened from Onus probandi incumbit ei qui dicit, non ei qui negat – the burden of proof lies with the one who speaks, not the one who denies) is the obligation on a party in a dispute to provide sufficient warrant for its position.
Holder of the burden
[edit]When two parties are in a discussion and one makes a claim that the other disputes, the one who makes the claim typically has a burden of proof to justify or substantiate that claim, especially when it challenges a perceived status quo.[1] This is also stated in Hitchens's razor, which declares that "what may be asserted without evidence may be dismissed without evidence." Carl Sagan proposed a related criterion – "extraordinary claims require extraordinary evidence" – which is known as the Sagan standard.[2]
While certain kinds of arguments, such as logical syllogisms, require mathematical or strictly logical proofs, the standard for evidence to meet the burden of proof is usually determined by context and community standards and conventions.[3][4]
Philosophical debate can devolve into arguing about who has the burden of proof about a particular claim. This has been described as "burden tennis" or the "onus game".[5][6][7]
Shifting the burden of proof
[edit]One way in which one would attempt to shift the burden of proof is by committing a logical fallacy known as the argument from ignorance. It occurs when either a proposition is assumed to be true because it has not yet been proven false or a proposition is assumed to be false because it has not yet been proven true.[8][9]
Proving a negative
[edit]A negative claim is the opposite of an affirmative or positive claim. It asserts the non-existence or exclusion of something.[10]
Logicians and philosophers of logic reject the notion that it is intrinsically impossible to prove negative claims.[11][12][13][14][15][10][16][17] Philosophers Steven D. Hale and Stephen Law state that the phrase "you cannot prove a negative" is itself a negative claim that would not be true if it could be proven true.[10][18] Many negative claims can be rewritten into logically equivalent positive claims (for example, "No Jewish person was at the party" is logically equivalent to "Everyone at the party was a gentile").[19] In formal logic and mathematics, the negation of a proposition can be proven using procedures such as modus tollens and reductio ad absurdum.[15][10] In empirical contexts (such as the evaluating the existence or nonexistence of unicorns), inductive reasoning is often used for establishing the plausibility of a claim based on observed evidence.[20][10][21] Though inductive reasoning may not provide absolute certainty about negative claims, this is only due to the nature of inductive reasoning; inductive reasoning provides proof from probability rather than certainty. Inductive reasoning also does not provide absolute certainty about positive claims.[19][10]
A negative claim may or may not exist as a counterpoint to a previous claim. A proof of impossibility or an evidence of absence argument are typical methods to fulfill the burden of proof for a negative claim.[10][22]
Application
[edit]In public discourse
[edit]Burden of proof is an important concept in the public arena of ideas. Once participants in discourse establish common assumptions, the mechanism of burden of proof helps to ensure that all parties contribute productively, using relevant arguments.[23][24][25][26]
In law
[edit]In a legal dispute, one party is initially presumed to be correct and gets the benefit of the doubt, while the other side bears the burden of proof. When a party bearing the burden of proof meets their burden, the burden of proof switches to the other side. Burdens may be of different kinds for each party, in different phases of litigation. The burden of production is a minimal burden to produce at least enough evidence for the trier of fact to consider a disputed claim.[27]: 16–17 After litigants have met the burden of production and their claim is being considered by a trier of fact, they have the burden of persuasion, that enough evidence has been presented to persuade the trier of fact that their side is correct. There are different standards of persuasiveness ranging from a preponderance of the evidence, where there is just enough evidence to tip the balance, to proof beyond a reasonable doubt, as in United States criminal courts.[27]: 17
The burden of proof is usually on the person who brings a claim in a dispute. It is often associated with the Latin maxim semper necessitas probandi incumbit ei qui agit, a translation of which in this context is: "the necessity of proof always lies with the person who lays charges."[28]
The party that does not carry the burden of proof carries the benefit of assumption of being correct, they are presumed to be correct, until the burden shifts after presentation of evidence by the party bringing the action. An example is in an American criminal case, where there is a presumption of innocence by the defendant. Fulfilling the burden of proof effectively captures the benefit of assumption, passing the burden of proof off to another party.
In statistics
[edit]In inferential statistics, the null hypothesis is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.[29] Rejecting or disproving the null hypothesis—and thus concluding that there are grounds for believing that there is a relationship between two phenomena (e.g. that a potential treatment has a measurable effect)—is a central task in the modern practice of science; the field of statistics gives precise criteria for rejecting a null hypothesis[citation needed].
The null hypothesis is generally assumed to be true until evidence indicates otherwise. In statistics, it is often denoted H0 (read "H-nought", "H-null", "H-oh", or "H-zero").
The concept of a null hypothesis is used differently in two approaches to statistical inference. In the significance testing approach of Ronald Fisher, a null hypothesis is rejected if the observed data are significantly unlikely to have occurred if the null hypothesis were true. In this case the null hypothesis is rejected and an alternative hypothesis is accepted in its place. If the data are consistent with the null hypothesis, then the null hypothesis is not rejected. In neither case is the null hypothesis or its alternative proven; the null hypothesis is tested with data and a decision is made based on how likely or unlikely the data are. This is analogous to the legal principle of presumption of innocence, in which a suspect or defendant is assumed to be innocent (null is not rejected) until proven guilty (null is rejected) beyond a reasonable doubt (to a statistically significant degree).
In the hypothesis testing approach of Jerzy Neyman and Egon Pearson, a null hypothesis is contrasted with an alternative hypothesis and the two hypotheses are distinguished on the basis of data, with certain error rates.
Proponents of each approach criticize the other approach. Nowadays, though, a hybrid approach is widely practiced and presented in textbooks. The hybrid is in turn criticized as incorrect and incoherent—for details, see Statistical hypothesis testing.
Statistical inference can be done without a null hypothesis, by specifying a statistical model corresponding to each candidate hypothesis and using model selection techniques to choose the most appropriate model.[30] (The most common selection techniques are based on either Akaike information criterion or Bayes factor.)
See also
[edit]References
[edit]- ^ Cargile, James (January 1997). "On the burden of proof". Philosophy. 72 (279). Cambridge University Press: 59–83. doi:10.1017/s0031819100056655. JSTOR 3751305. S2CID 170772287.
- ^ Marc Kaufman, First Contact: Scientific Breakthroughs in the Hunt for Life Beyond Earth, Simon and Schuster, p. 124.
- ^ Leite, Adam (2005). "A localist solution to the regress of justification". Australasian Journal of Philosophy. 83 (3): 395–421 [p. 418]. doi:10.1080/00048400500191974. S2CID 170261121.
[t]he point of articulating reasons in defense of one's belief is to establish that one is justified in believing as one does.
- ^ Leite, Adam (2005). "A localist solution to the regress of justification". Australasian Journal of Philosophy. 83 (3): 395–421 [p. 403]. doi:10.1080/00048400500191974. S2CID 170261121.
justificatory conversation...[is]...characterized by a person's sincere attempt to vindicate his or her entitlement to a belief by providing adequate reasons in its defense and responding to objections.
- ^ Dennett, Daniel C. (July 1988). "Review of Psychosemantics by Jerry Fodor". The Journal of Philosophy. 85 (7): 384–389 (389). doi:10.2307/2026956. JSTOR 2026956.
Fodor is too wise to think his series of arguments can flat disprove the claims of the opposition, so time and again he resorts to claims about shifting the burden of proof, begging the question, outsmarting by embracing the conclusions of reductios, and other exploitations of the rules of the game. The book is a tireless exercise of that philosopher's pastime, burden-tennis. Burden, burden, who has the burden of proof now? Fodor mostly plays solitaire burden-tennis, against an imaginary opponent often personified as Granny or Aunty, which permits him to express the opposition view in terms that suit his rebuttal, without having to address the issue of whether this is a sympathetic rendering of any real opponent's claims.
- ^ Rodych, Victor (1996) [1986]. "Wittgenstein's inversion of Gödel's theorem". In Shanker, Stuart; Kilfoyle, David (eds.). Ludwig Wittgenstein: critical assessments. Vol. 2. The later Wittgenstein: from Philosophical investigations to On certainty. London; New York: Routledge. pp. 232–265 (261). ISBN 0415149150. OCLC 47938413.
Thus, in 1991 Wang seems to understand why Wittgenstein rejects GIT, but, apparently favouring the "onus game" (or "burden tennis"), he unfortunately concludes (pp. 257–58) that "the burden of proof falls ... squarely on Wittgenstein's side" because of Wang's own 'principle of presumed innocence'.
- ^ Abelson, Robert P. (1995). "Credibility of argument". Statistics as principled argument. Hillsdale, NJ: Lawrence Erlbaum Associates. p. 170. ISBN 0805805273. OCLC 31011850.
When research presentations advance claims that many or most readers deem incredible, these claims are vulnerable to severe challenge. In response, there will typically be a rebuttal by the investigator, and then a fresh round of criticism. The burden of proof shifts back and forth between the investigator and the critic in what might be called the game of 'burden tennis'.
- ^ "Argumentum ad Ignorantiam". Philosophy 103: Introduction to Logic. Lander University. 2004. Archived from the original on 30 April 2009. Retrieved 2009-04-29.
- ^ Dowden, Bradley. "Appeal to ignorance". Internet Encyclopedia of Philosophy. Retrieved 2016-02-24.
- ^ a b c d e f g Hales, Steven D. (Summer 2005). "Thinking tools: You can prove a negative" (PDF). Think. 4 (10). Cambridge University Press: 109–112. doi:10.1017/S1477175600001287. S2CID 170305277.
- ^ Hales, Steven D. (17 December 2012). This Is Philosophy: An Introduction. John Wiley & Sons. ISBN 978-0-470-65883-3.
- ^ Gusfield, Dan (18 January 2024). Proven Impossible: Elementary Proofs of Profound Impossibility from Arrow, Bell, Chaitin, Gödel, Turing and More. Cambridge University Press. ISBN 978-1-009-34950-5.
- ^ Saunders, Kevin W. (1984–1985). "The Mythic Difficulty in Proving a Negative". Seton Hall Law Review. 15: 276.
- ^ Steiner, Robert A. (1999). "I Am Not a Giraffe, and I Can Prove It". ETC: A Review of General Semantics. 56 (3): 292–295. ISSN 0014-164X. JSTOR 42705762.
- ^ a b Russell, Gillian (1 December 2015). "The Justification of the Basic Laws of Logic". Journal of Philosophical Logic. 44 (6): 793–803. doi:10.1007/s10992-015-9360-z. ISSN 1573-0433. S2CID 254739046.
- ^ Rich, Elaine; Cline, Alan Kaylor. Is It Really Impossible to Prove a Negative?.
- ^ Law, Stephen (1 April 2011). Believing Bullshit: How Not to Get Sucked into an Intellectual Black Hole. Prometheus Books. ISBN 978-1-61614-412-8.
- ^ "You Can Prove a Negative | Psychology Today". www.psychologytoday.com.
- ^ a b Enos, Ryan D.; Fowler, Anthony; Havasy, Christopher S. (September 2017). "The Negative Effect Fallacy: A Case Study of Incorrect Statistical Reasoning by Federal Courts". Journal of Empirical Legal Studies. 14 (3): 618–647. doi:10.1111/jels.12158. ISSN 1740-1453. S2CID 53063085.
- ^ Jawlik, Andrew A. (24 October 2016). Statistics from A to Z: Confusing Concepts Clarified. John Wiley & Sons. ISBN 978-1-119-27203-8.
- ^ "6.3: Proving Your Conclusion". Humanities LibreTexts. 28 November 2019.
- ^ Damer, T. Edward (2009). Attacking faulty reasoning: a practical guide to fallacy-free arguments. Cengage Learning. p. 17. ISBN 9780495095064.
- ^ Goldman, Alvin (1994). "Argumentation and social epistemology". The Journal of Philosophy. 91 (1): 27–49. doi:10.2307/2940949. JSTOR 2940949.
- ^ van Eemeren, Frans H.; Grootendorst, Rob (2004). A systematic theory of argumentation. Cambridge, UK; New York: Cambridge University Press. p. 60. ISBN 0521830753.
[t]here is no point in venturing to resolve a difference of opinion through an argumentative exchange of views if there is no mutual commitment to a common starting point.
- ^ Brandom, Robert (1994). Making it explicit. Cambridge, MA: Harvard University Press. p. 222. ISBN 067454319X.
[t]here are sentence types that would require a great deal of work for one to get into a position to challenge, such as 'Red is a color,' 'There have been black dogs,' 'Lightning frequently precedes thunder,' and similar commonplaces. These are treated as 'free moves' by members of our speech community—they are available to just about anyone any time to use as premises, to assert unchallenged.
- ^ Adler, Jonathan E. (2002). Belief's own ethics. Cambridge, MA: MIT Press. pp. 164–167. ISBN 0262011921.
- ^ a b Criminal Law – Cases and Materials, 7th ed. 2012, Wolters Kluwer Law & Business; John Kaplan, Robert Weisberg, Guyora Binder, ISBN 978-1-4548-0698-1, [1]
- ^ Transnational principle of law: Trans-Lex.org
- ^ Everitt, Brian (1998). The Cambridge Dictionary of Statistics. Cambridge, UK New York: Cambridge University Press. ISBN 0521593468.
- ^ Burnham, K. P.; Anderson, D. R. (2002), Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.), Springer-Verlag, ISBN 0-387-95364-7.