Metaphor identification and MIP

As regards to metaphor identification, Musolff (2004: 64f) maintains that finding metaphors in a large amount of data can be fairly difficult. He looks at approaches such as tuning devices, which are expressions that can help to identify metaphors, for example sort of, so to speak, figuratively speaking (cf. Cameron and Deignan (2003)). However, such expressions are neither the exclusive way of identifying metaphors in corpora, nor sufficient. Musolff (ibid.) emphasises that databases are

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‘blind’ and cannot directly identify metaphorical expressions without also finding non-metaphorical expressions. Random internet searches are characterised as not helpful for corpus analyses where the range and genres of material are of importance for the outcome of frequency and conceptual range of metaphor usage (see Musolff (2004: 66), Deignan (2005), Cameron and Low (1999)). The main conclusion Musolff (ibid.) draws in his chapter about corpora and the semantics of metaphor is that small, specialist corpora can be helpful in identifying metaphors because the specialised corpus minimises the amount of information the researcher has to go through. So it can be said that Musolff’s arguments indirectly support the corpus and methods chosen in this PhD study because using smaller, specialised corpora for metaphor analysis is presented as heuristically most effective.

Besides the reflections on metaphor identification the first theory dedicated to this aspect is the so-called Metaphor Identification Procedure (MIP), developed by a group of researchers, Pragglejaz (2007):

“This article presents an explicit method that can be reliably employed to identify metaphorically used words in discourse. Our aim is to provide metaphor scholars with a tool that may be flexibly applied to many research contexts.” (p. 1).

Their purposes are to explicate whether or not something is metaphorical and to provide a reliable tool for metaphor scholars to identify metaphors in discourse. The quality and usefulness of this method will be measured against the authors’ own statements. They firstly introduce their method, apply it to an example and formulate some remarks on reporting the results of using the MIP. Their relatively long list becomes clearer when they start to apply it to an example text, see Pragglejaz (2007: 3). The whole procedure consists of four steps. First, the whole text under analysis should be read. This already shows that this is part of a qualitative analysis or the discussion of individual examples in a larger corpus. The next steps are a semantic and a lexical analysis. Lexical units should be recognized and marked, e.g. by a slash (/), similar to how it is sometimes done in a sentence to find the syntactic elements. Then, the meaning will be analysed. Establishing the contextual meaning first does this. The contextual meaning can be determined for example by describing how the lexical unit describes an entity or the situation that is evoked by the text. Then, the contextual meaning is compared to the basic

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meaning, which can deviate from the contextual meaning in the following ways (cf. ibid.):

“—More concrete [what they evoke is easier to imagine, see, hear, feel, smell, and taste];

—Related to bodily action;

—More precise (as opposed to vague); —Historically older”.

Based on these criteria, the contextual and basic meanings will be compared and there will be a decision on the question whether these meanings deviate from each other. The fourth step of this procedure merely reads “If yes, mark the lexical unit as metaphorical.” (ibid. p. 3). This refers to the question of whether the contextual meaning (what the lexical unit concretely expresses in this text) differs from the basic meaning, which was defined by the criteria or dimensions that make it differ from the contextual meaning, as listed above.

How should the results be reported – according to MIP? Pragglejaz (2007: 13) point out that the main purpose of this method of recognition and analysis of metaphor is to have an explicit set of steps so that it is possible to locate where exactly the point or cause of disagreement among different researchers lies.

The second aspect mentioned concerns forms of meta data that could give additional information on the text, such as number of words, genre, readership etc. and as much context as possible. These aspects are also mentioned in the corresponding passage about reporting the results:

“For any metaphor identification project, we urge that researchers report their results as fully as possible by including, as much as practically possible, details about the texts studied, the readership assumed, the determination of lexical units, resources used to aid decisions in completing the steps of the MIP, specific coding decisions, who the analysts were, and the statistical reliability of the analysis. Resources that we recommend are large electronic corpora and corpus- based dictionaries.” (ibid.).

Researchers are urged to give as much context as possible with their results, coding discussion and even statistical reliability of the analysis. For these purposes, the Pragglejaz team (ibid.) recommend large electronic corpora and corpus-based dictionaries.

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Pragglejaz (2007) proved to be a good method for systematising the process of identifying metaphors. It remains the only universally and easily usable metaphor identification procedure despite the publication by Steen et al. (2010: 13f), who introduces the MIPVU (Metaphor Identification VU University) procedure. It lacks the simplicity of the MIP procedure from 2007 while giving no added value for identifying metaphors. In the given passage (ibid. p. 13f), Steen explains his MIPVU procedure:

“1. Find local referent and topic shifts.

Good clues are provided by lexis which is "incongruous" (Cameron 2003; Charteris-Black 2004) with the rest of the text.

2. Test whether the incongruous words are to be integrated within the overall referential and/or topical framework by means of some form of comparison. Good clues are provided by lexis which flags the need for some form of similarity or projection (Goatly 1997).

3. Test whether the comparison is nonliteral or cross- domain.

Cameron (2003: 74) suggests that we should include any comparison that is not obviously non- metaphorical, such as the campsite was like a holiday village. Whenever two concepts are compared and they can be constructed, in context, as somehow belonging to two distinct and contrasted domains, the comparison should be seen as expressing a cross- domain mapping. Cameron refers to these as two incongruous domains.

4. Test whether the comparison can be seen as some form of indirect talk about the local or main referent or topic of the text. (If it is not, we might be dealing with a digression.)

A provisional sketch of a conceptual mapping between the incongruous material functioning as source domain on the one hand and elements from the co- text functioning as target domain on the other should be possible. This type of preliminary conceptual analysis is useful because this is a case of direct metaphor where it is impossible to look up the metaphorical meaning of indirectly used words in the dictionary, as is possible for almost all indirect metaphor.

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5. If the findings for tests 2, 3, and 4 are positive, then a word should be identified as (part of) a direct form of metaphor.”

Points one and two of Steen’s five-step procedure are very similar to Pragglejaz’s procedure hence it can be said they add nothing new but summarise the known approach by Pragglejaz into his own theory. Whether the aspects to look for in a text are referred to as "incongruous" or as basic and contextual meaning that contrast are just different names for the same thing: the two meanings in a metaphor that contrast or differ in context. Points three to four from his procedure are very general and hence not necessarily helpful from a practical perspective. Both the notions of directness vs. indirectness as well as the questions to what extent a comparison is ‘literal’ or ‘non-literal’ remain unclear.

As a conclusion, it can be said that the MIP by Pragglejaz (2007) turned out to be the most helpful method for identifying, discussing and documenting metaphor in discourse (in a corpus) in order to have a standardized and explicit set of principles that helps to locate where the potential point of disagreement is.

Lakoff and Johnson (1980) focus on cognitive explanations about metaphor, but their examples are not taken from a representative corpus in any sense. This point is also criticised by Goschler (2008: 34). Therefore, it will be ensured that corpus evidence will be exploited in this study, more than so-called ‘armchair reflections’, introspective speculation without concrete examples or evidence of actual language use, as McEnery and Wilson (1996: 15) put it.