Abstract of Plausibility Study, 6th November 2021
The links do not lead to translations, but it is perhaps possible to translate sections of particular interest using the Internet. Suggested citation: Sponsel, Rudolf (6/11/2021) Abstract of Plausibility Study. Internet Publication for General and Integrative Psychotherapy (IP-GIPT): https://www.sgipt.org/wisms/sprache/BegrAna/Plausib/RSEUPT-Engl.htm
Source material: From the analysis of the research literature, especially Rescher 1976, and the analysis of the examples of use, and based on the results of my empirical pilot study, I have come to the following key finding: the term "plausible" or "plausibility" is in very many contexts of science and life used as an undefined and usually functional basic term that is considered in layman's terms with the following core characterisations: reasonable, understandable, believable, coherent, correct, possible, probably true. However, most attempts to clarify the term come to nothing if one looks closely, because an unclear term such as plausible gets shifted onto other, just as unclear terms, etc., etc. This gives rise to entire "terminology transformer stations" , which is particularly typical in the humanities, law, and the social and cultural sciences.
Before defining plausibility, a precise analysis of the term is useful. It is difficult, but necessary. Plausible is a metalinguistic expression of at least the 2nd level, because every plausibility assessment includes reasons1 that belong to the first metalinguistic level. The more important terms are indexed for clarity and ease of understanding: object language0 metalanguage1, metalanguage2, metalanguage3... A metalanguage does not describe facts1 in the world (worlds), e.g., there is0 a tree (so-called object language0), but assesses the descriptions of the facts1, e.g., it is correct1 (false1, doubtful1, nonsense1) that there is a tree0. Metalanguage1 1st level: There is a draft because1 the door and windows are open0. Metalanguage2 2nd level: it is plausible2 that there is a draft because1 the door and windows are open. Objectlanguage0: it is0 hot; the door and windows are0 open. Metalanguage1 1st level: The door and windows0 are open, because1 it is hot0. Metalanguage2 2nd level: it is0plausible2 that the door and windows are open0 because1 it is hot0."Because1" cannot be perceived directly; the causal relationship is an epistemological construction. And, further, metalanguage3 3rd level: I don't see3 why that is supposed to be plausible2. Here, a discussion3 about a plausibility assessment2 is therefore taking place.
The basic idea: whether or to what extent something is judged to be plausible2 depends on the reasons1 for or against a circumstance1 that are put forward. This initially raises the important question of what a reason1 is supposed to consist of.
A reason1, a metalinguistic term of the 1st level, consists of allj circumstances1 that, to a greater or lesser degree, have a supportive or hampering effect on other circumstances1. Causality1, probability2, prevalence1, regularities1 and lawlike characteristics1 play an important role in those reasons1, as do experiences0 and what has already been lived through0. All criteria supporting the truth1 or falsehood1 of circumstances1 can also play an important role for plausibility2.
The first basis for plausibility2 is therefore the number of reasons1 that are asserted for or against a circumstance1. Although a single reason1 is sometimes sufficient, as a rule, not all reasons1 are equivalent, and so the important question of how the reasons1 are to be weighted2, or more precisely, how one can justify different weights2 must be answered. This can be easy if the reason1 is, for example, prevalence1. Then, one can equate weight2 and prevalence1. Once can proceed in a similar way with probabilities1. Another idea is to use the predictive value1 when predictable circumstances1 are in question: then the weights2 that enable the best possible forecast1 would be good. The work on argumentation schemes, e.g., by Walton et al. (2008), can provide important assistance in recording and assessing reasons. Given the current state of knowledge, where hardly any standard models have been analysed and calculated, one will have to be content with asking for justifications so that these can be examined critically.
This brings me to my proposal for a definition of plausibility2:
D1: A circumstance1 is plausible2 (pl) to the extent that more heavily weighted2 reasons1 G+ can be stated for it and less heavily weighted2 reasons1 G- can be stated against it.
Basically, reasons1 can have four modalities1: they can have a positive (+), a negative (-), a both positive and negative (+ -) and a questionable, unclear, indeterminate (?) effect. An overall plausibility assessment2 (PL) for a circumstance1 would thus consist of a fourfold representation: +, -, + -, ?. In practice, one will often be able to restrict oneself to the first two modalities (reasons1 for and reasons1 against), and so, ultimately, one is provided with a plausibility formula, because the one always results from the other:
pl+ = (G+) / (G+ + G- )
pl- = 1 - pl+
General example: If the weighted2 reasons1 G+ for a circumstance1 result, for example, in G+ = 3, and if the weighted2 reasons1 G- against this circumstance1 result in G- = 1, then, when inserting the absolute numbers, one obtains pl+= (3) / (3+1) = 3/4 or pl+ = 0.75 and thus for pl- = 1 - 0.75 = 0.25.
Concrete example (EA31): assuming that the following pertains for the weighted2 reasons1: G+ (the road is0 wet because1 it has rained) = 998, G-(the road is0 wet for other reasons)= 27, then the plausibility for pl+ (the road is0 wet because1 it has rained) = (998) / (998 + 27) = 998/1025 = 0.974 and pl-(the road is0 wet for other reasons) = 1 - 0.974 = 0.026.
Scale problem: When using the basic mathematical operations (addition, subtraction, multiplication, division), it is a prerequisite that the numerical values are at least on the interval scale level, which is hardly achievable. The important intermediate range between the ordinal and interval scales was neither recognised nor resolved by Stevens (1946). One can interpret the numerical values as correspondingly weaker (on the quasi or fuzzy interval scale) and pragmatically prove their usefulness for justification.
Key words for plausibility research: plausibility, argumentation, everyday logic, evidence theory, belief, credibility, believability.
On the importance of plausibility2 in German-language science > Koch, though he overlooked Kienpointner's Alltagslogik ("everyday logic") from 1992, Schill's entry in the Wörterbuch der Kognitionswissenschaften ("dictionary of cognitive sciences") (1996), and the informative entry in the Historisches Wörterbuch der Rhetorik (the "historical dictionary of rhetoric" – HWR). My analysis, among other things, in logic, the theory of science and philosophy shows that the term plausible or plausibility is often used, but is almost never explained or justified (exception: Kienpointner, HWR). The international publishing programme of DeGruyter alone contains over 10,000 practical examples from all areas of science, only a few of which are included in my investigation.
Things were different in the USA. There was extensive plausibility research there, as Schmidt-Scheele's bibliography shows, whereby I would particularly like to emphasise Rescher's Plausible Reasoning from 1976 and Walton's Plausible Argument from 1992.
Many linguistic regions (e.g., Asia, Australia, Oceania, South and Central America, Africa, Arab regions, Europe) could not be taken into account due to a lack of linguistic knowledge, and so I also cannot say anything about those. My statements can therefore only apply to my sources. The intellectual achievements of small peoples and minorities (e.g., indigenous peoples) are unfortunately often not taken into account in science.
Results (a selection) of my non-representative empirical pilot study: for 52 compilers, 24 characteristics were examined with respect to the question: How much of that characteristic is contained in the term plausible? 21 reasons were also asked, specifying a rule with an explanatory example. In terms of assessments, 9 choices were possible for the 24 characteristics and the 21 reasons: 0, 1, 2, 3, 4, 5, 6, 7, ?. The choices of characteristics and reasons by all; age, gender, school education and occupational group as well as for all were evaluated in a differentiated manner, and, very remarkably, it turned out that there were no major differences in the assessments. To most people, a circumstance1 appears to be all the more plausible2 the more verifiable and examinable reasons1 there are for its materialisation. What is plausible2 must not contradict proven experiences1 and must also not contain any contradictions1 itself. In total, 52 extremely valuable documents relating to the psychology of thought processes are available, whose full evaluation will take a while still. In addition, a multivariate correlation and eigenvalue analysis was carried out, which, even so, yielded 17 almost-linear dependencies (almost collinearities), most strikingly in the connection between the reasons1 35-36.
Term base for the definition of plausible: argument, assessment classes, formula, function, lawlikeness, weight, weighting problem, reason, prevalence, causality, metalanguage(s), possibility, usefulness, object language, pragmatic, facts, overall plausibility assessment, framework, regularity, scaling problem, probability, effect.
It is important to ensure that the terms of the term base are clearly defined in order to limit terminology transformer stations, the great vice of the humanities, law, and the social and cultural sciences (>language criticism). If definitions are too difficult, one can help oneself with typical examples and counterexamples, preferably in a concrete-operational manner with referencing. Many problems can be solved as soon as one becomes concrete-operational and not only opines.