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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 all_j 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.

Plausibility research
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.

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