El proceso participativo de formulación

The method reported in this chapter attempts to do something slightly different from previous investigations which explore the relationship between clusters and authorial style. Rather than simply identifying clusters, a decision was made to focus only on those clusters which can be argued to be formulaic for an author because of their recurrence across a minimum threshold of texts and these formulaic clusters were assessed for distinctiveness in comparison to other authors. Using the Jaccard’s coefficient statistical test proved successful in demonstrating that formulaic clusters were consistent and distinctive for authors, leading to the conclusion that authors can be differentiated based on their use of formulaic clusters. In this regard, support could be provided for the first and second hypotheses. However, it became more difficult to actually attribute a Questioned Document to its correct author through the ensuing descriptive approach; a situation which became further compounded when fewer texts were available for analysis. Therefore, whilst it would be wrong to suggest that support was definitely provided for the third hypothesis, some areas of commonality between the Questioned Document and the texts produced by the candidate authors could be identified. It is this potential in the method which may prove to be a foundation for future research into this special type of cluster.

As expected, reducing the number of texts available for analysis means that fewer formulaic clusters are identified. The significance of this is that the method outlined in this chapter will clearly carry more investigative value if larger data sets are available for analysis and it is perhaps not a suitable approach for those investigations where fewer/shorter texts are available. Whilst it may not be possible to speculate about the ideal number of texts that would be required to make the method more robust, it is important to note that no reliable predictions could be made about which particular clusters might occur in another random text, since no formulaic cluster was used sufficiently frequently or regularly. If any of the formulaic clusters had occurred more than once in all five of the texts for an author, there may be grounds to predict that the cluster would also occur in a sixth, seventh or nth text also by that author. But since this situation did not occur, the fact that the

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next best formulaic clusters, those occurring in four out of five texts, already means that 20% of the texts produced by an author will not contain that cluster.

Likewise, it is likely that the length of the texts available for an investigation will affect analysis based on this method. Whilst Grant (2011) had considerably more texts available during his analysis (407 texts produced by known authors), it is less likely that a feature such as formulaic clusters would have had sufficient opportunity to manifest in short-form communications such as SMS text messages. A forensic linguist may therefore first need to appraise their data and then decide whether a method such as this is appropriate to use. The method cannot therefore claim to be applicable to all types of texts.

One final issue that has not received attention in this chapter since it falls outside the scope of the research is the actual number of formulaic clusters that were identified for each author—only those formulaic clusters that occurred in a Questioned Document have been explored in detail. However, should any significance be attached to the fact that 26 formulaic clusters (based on at least one occurrence in three out of five texts) were identified for Rose, whilst only one was identified for Michael, or 12 for Elaine but only four for Sarah (see Table 5.3)? It is likely that this level of recurrence would create the sense of a repetitive style for Rose and presumably more novel language and less repetition for Michael. This in itself may provide a useful avenue for future investigation.

5.4.1 Is the method valid?

The case has been made in this chapter that formulaic clusters are valid as evidence of formulaic sequences since they recur across a series of texts; they therefore hold potential to be pre-fabricated in these particular forms, ready for use when required. In other words, the authors have found them to be communicatively useful. Whilst some of the formulaic clusters may appear to be quite acceptable as evidence of formulaic sequences (e.g. the whole thing, the next day, as a result, in the end, all the time), others, due to their semantic incompleteness, appear less so (e.g. it was a, and I just, to go to, out of the, me and my). There are certainly features in common with previous research into formulaic language. Notably, Wray (2002) and those who use the formulaic sequence as their definition of choice, do not see the lack of meaning (in other words, the fact that the units are incomplete) as a problem. Therefore, the fact that formulaic clusters such as it is a, and I was, and I was really are incomplete does not preclude them from being formulaic. They are, though, certainly less intuitively satisfying. A stronger argument for the classification of these clusters as formulaic is based on the frequency approach to formulaic language (cf. Section 3.5.2, p. 70). That is, they occur

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over a certain threshold for a particular author and can therefore be argued to be formulaic for a particular individual based on their recurrence in texts. In other words, the individual has found a particular formulaic cluster which enables them to express their meaning, or produce cohesive discourse, in a way which operates best for them. In this way, formulaic clusters can be argued to be formulaic sequences. However, claiming that a formulaic cluster is a formulaic sequence just because it occurs in at least three texts is clearly arbitrary and entirely different results will be obtained if this threshold is changed. The key point perhaps lies less in whether the formulaic clusters identified in this research can be argued to be formulaic sequences and more in their diagnostic potential as a tool for the forensic linguist.

5.4.2 Is the method reliable?

Quite whether the method outlined in this chapter is reliable is not clear. There are elements of the analysis which are automated, and as such, are completely replicable leading to high reliability. However, an element of linguistic decision making is also introduced which can only be performed by a linguist as opposed to a computer, and is therefore subject to the usual fallibilities (cf. Section 3.5.1). The most obvious example is the decision to exclude formulaic clusters which appear to be context-specific. Furthermore, whilst demonstrating distinctiveness could be achieved through an automated approach, a forensic linguist is required to assess the output in order to make an attribution. Whilst a skilled forensic linguist may well reach the same conclusions time and time again, there is nothing to mitigate against the possibility that other forensic linguists might reach different conclusions (e.g. Finegan, 1990).

5.4.3 Is the method feasible for forensic purposes?

It has already been established that the method outlined here is unlikely to be universally applicable. Therefore, selecting formulaic clusters as a marker of authorship will not be appropriate for every type of forensic investigation (but then, neither is selecting other text-specific features such as initialisms in text messages which would be inappropriate for academic essays). It is also important to point out that the specific formulaic clusters identified here will not be applicable to other cases. In other words, the fact that 93 formulaic clusters were identified and used in the analysis does not mean that the same 93 formulaic clusters can be used in other forensic investigations. Clearly, the selection of formulaic clusters will rest entirely on the texts available for analysis, and the clusters occurring within.

In light of this, the bigger issue raised is whether the formulaic clusters identified based on the five texts available for each author would also be identified if a different set of texts by the same

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authors had been used. Since it is claimed that these clusters are formulaic, it is hoped that they would, but this is unlikely since any text will only exemplify a very small number of formulaic clusters. In reality, the fact that many of the clusters occurred in no more than two texts by the same authors leaves three texts remaining where the formulaic cluster was not used. If the Questioned Document happens to be one of those texts where the author does not use a particular (set of) formulaic clusters, then the analysis is no longer applicable (speaking of course only about the qualitative attribution phase, since, as explained earlier, the justification for using Jaccard’s co-efficient is that non-occurrence is not taken into consideration). It is therefore unlikely that this method, in its current state, is forensically robust. It is also not an insignificant fact that the texts used in this investigation are short and so the range of formulaic clusters which have had the opportunity to manifest may be limited. Just as lowering the threshold increased the number of formulaic clusters that were identified, presumably, increasing the lengths of the texts would also lead to a larger quantity of formulaic clusters.

In conclusion, the method has shown some promise at demonstrating consistency and distinctiveness between authors, but far more research into the area would be required before the method is forensically robust and, as an initial suggestion, longer texts may need to be the focus of future research.