Abstract
Argument analysis is a powerful tool for structuring policy deliberation and decision-making, especially when complexity and uncertainty loom large. Argument analysis seeks to determine which claims are justified or criticized by a given argumentation, how strong an argument is, on which implicit assumptions it rests, how it relates to other arguments in a controversy, and which standpoints one can reasonably adopt in view of a given state of debate. This chapter first gives an overview of the activities involved in argument analysis and discusses the various aims that guide argument analysis. It then introduces methods for reconstructing and evaluating individual arguments as well as complex argumentation and debates. In their application to decisions under great uncertainty, these methods help to identify coherent positions, to discern important points of (dis)agreement, as well as to avoid spurious consensus and oversimplification.
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Notes
- 1.
An “argumentative turn” in policy analysis and planning had first been proclaimed by Fisher and Forester (1993), who called for putting more emphasis on deliberative and communicative elements in decision making (see also Fischer and Gottweis 2012). We conceive of our chapter, and this book in general, as a genuinely normative, argumentation-theoretic contribution to – and extension of – the programme of an argumentative turn, which was so far mainly shaped by the perspectives of political science and empirical discourse analysis.
- 2.
For examples, see Singer (1988:157–9).
- 3.
- 4.
We use “debate” in a sense which does not necessarily involve more than one person. One can “internalize” proponents of various positions and explore how they can argue against each other.
- 5.
Sometimes “serial” or “subordinate” are used in place of “hierarchical”, and “convergent” in place of “multiple”. See Snoeck Henkemans (2001) a survey on terminology and basic structures of complex argumentation.
- 6.
We use “inference” as a technical term for completely explicit and well-ordered arguments.
- 7.
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- 9.
With p corresponding to “the animal is like us”, q to “there is no reason for performing the experiment” and r to “we ought not to perform on the animal an experiment that would be considered outrageous if performed on one of us.”
- 10.
Of course, reconstructing enthymemes does not rest on the highly dubious idea that all implicit information should be made explicit. Even complete arguments virtually always involve a great deal of presuppositions. That the premise “The 2-degree-target can no longer be achieved”, as well as its negation, imply “Reaching the 2-degree-target is not impossible at every point in time” does not mean that the latter sentence should be reconstructed as an additional premise.
- 11.
In fact, missing conclusions are often neglected in the literature.
One alternative to the traditional approach relies on argument schemes and adds the elements needed to turn the argument at hand into an instance of such a scheme (Paglieri and Woods 2011). Another idea is to interpret arguments against the background of a belief-state ascribed to its author and deal with “incomplete” arguments by revising the ascribed belief state (Brun and Rott 2013).
- 12.
This presupposes that charity is interpreted as a presumptive principle, not merely a tie-breaker.
As Jacquette (1996) has pointed out, adding a premise is in some cases less charitable than strengthening a premise or weakening the conclusion.
- 13.
Sentence S is logically stronger than sentence T (and T is logically weaker than S) just in case S implies T but not vice versa.
- 14.
Other inconsistencies, e.g. inconsistency of a premise with known facts of science, are just a reason for assessing the premise in question as false.
- 15.
In an undercut argument, the proponent (who puts forward the argument) uses premises which the opponent accepts to infer a conclusion which the opponent denies. See Betz (2013) for a typology of dialectical moves.
- 16.
The distinction between deductive and non-deductive primarily applies to standards of evaluation and only derivatively to arguments. An arguments can then be called “deductive” either because it is meant or taken to be evaluated by deductive standards, or because it performs well with respect to deductive standards. (Skyrms 2000:ch. II.4).
- 17.
In this chapter, we use “validity” simpliciter as an abbreviation for “deductive validity”; in the literature it often also abbreviates “formal validity”.
- 18.
Lumer (2011) explains how argumentation schemes can be exploited for deductivist reconstructions.
- 19.
There is a rich literature on fallacies; see section Resources. For specific fallacies in argumentation about risk, see Hansson (2016).
- 20.
Harsanyi offers further considerations which may dispel the straw-man worry in the text that follows what we quoted as [Harsanyi].
- 21.
This is a restricted perspective since there are other types of non-descriptive sentences as well, for example those which include evaluative terms (“good”, “better”). For a more precise and sophisticated discussion (using a different terminology), see Morscher (2013).
- 22.
Strictly speaking, this is only true for practical arguments in which every premise and the conclusion either is entirely in the scope of a deontic modality or does not contain any deontic modality. The situation is much more complex if for practical arguments which include “mixed” sentences; that is, sentences only part of which are in the scope of a deontic modality. See Morscher (2013) for an accessible discussion.
- 23.
Pollock (1987:485) distinguishes two further dialectic relations. An argument rebuts another argument if the arguments possess contradictory (or at least contrary) conclusions; an argument undercuts another argument if it questions the validity or applicability of an inference scheme applied in the latter. (Note that this is another use of “undercut” than in footnote 15.) The undercut relation is, however, not directly relevant in the framework we propose here. Validity of the individual arguments is guaranteed qua charitable reconstruction. Rather than using controversial inference schemes for the reconstruction, we suggest to add corresponding general premises that can be criticized. Pollock’s undercut-relation hence effectively reduces to the attack relation.
- 24.
The proper analysis and evaluation of non-deductive reasoning poses serious theoretical problems and goes beyond the scope of this chapter. For a comprehensive state-of-the-art presentation compare Spohn (2012).
- 25.
A prominent rival approach to the one presented in this chapter are Dung-style evaluation methods for complex argumentation, which have been developed in Artificial Intelligence over the last two decades (see Bench-Capon and Dunne 2007; Dung 1995). Dung-style evaluation methods impose far-reaching rationality constraints; e.g. non-attacked arguments must be accepted, and undefended arguments must not be accepted. According to the approach championed in this chapter, in contrast, any argument can be reasonably accepted, as long as the proponent is willing to give up sufficiently many beliefs (and other arguments).
- 26.
Sometimes one and the same (“prima facie”) normative principle, when applied to a complex decision situation, gives rise to conflicting implications. This is paradigmatically the case in dilemmatic situations, where one violates a given norm no matter what one does. In argument-mapping terms: given all descriptive premises are accepted, there is no coherent position according to which the “prima facie” principle is true. In regard of such cases, we suggest to systematize the aggregation and balancing process through specifying the normative principle in question such that the differences between alternative choices are made explicit. E.g. rather than arguing with the principle “You must not lie” in a situation where one inevitably either lies to a stranger or to one’s grandma, one should attempt to analyze the reasoning by means of the two principles “You must not lie to relatives” and “You must not lie to strangers”, which can then be balanced against each other.
- 27.
“Yes” stands for statement accepted; “no” for statement not accepted. For the sake of simplicity, we do not distinguish between denying a statement and suspending judgement.
- 28.
This section is adapted from http://www.argunet.org/2013/05/13/mapping-the-climate-engineering-controversy-a-case-of-argument-analysis-driven-policy-advice/ [last accessed 16.03.2015].
- 29.
On the ethics of climate engineering and the benefits of argumentative analysis in this field compare Elliott (2016).
- 30.
Steele (2006) interprets the precautionary principle as a meta-principle for good decision-making which articulates essentially these two requirements.
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Resources Supporting Argument Analysis
Resources Supporting Argument Analysis
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Bowell, Tracy, and Gary Kemp. 2015. Critical Thinking. A Concise Guide. 4th ed. London: Routledge.
Chapter 5 gives a very accessible yet reliable introduction to techniques of argument reconstruction focusing on the analysis of individual arguments and complex argumentation.
Two online tutorials focusing on analysing complex argumentation are:
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Course “Argument Diagramming” at Carnegie Mellon University: http://oli.cmu.edu/courses/free-open/argument-diagramming-course-details/.
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Critical Thinking Web: http://philosophy.hku.hk/think/.
A more extensive treatment of fallacies can be found in the Internet Encyclopedia of Philosophy: http://www.iep.utm.edu/fallacy/.
Argunet is an argument mapping software designed to support the reconstruction of complex argumentation and debates: http://www.argunet.org/.
Links were correct on 22.07.2015.
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Brun, G., Betz, G. (2016). Analysing Practical Argumentation. In: Hansson, S., Hirsch Hadorn, G. (eds) The Argumentative Turn in Policy Analysis. Logic, Argumentation & Reasoning, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-30549-3_3
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