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Literary and Linguistic Computing Advance Access originally published online on July 20, 2009
Literary and Linguistic Computing 2009 24(4):403-416; doi:10.1093/llc/fqp026
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© The Author 2009. Published by Oxford University Press on behalf of ALLC and ACH. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Untangling the derivatives: points for clarification in the findings of the Shakespeare Clinic

Thomas Merriam

Correspondence: Thomas Merriam 35 Richmond Road, Basingstoke RG21 5NX, UK. E-mail: merriam12484648{at}hotmail.co.uk

   Abstract

The work of the Shakespeare Clinic of Claremont McKenna College, led by Ward E.Y. Elliott and Robert J. Valenza, is recognized for its pioneering computer analysis of many early modern texts to determine whether William Shakespeare (1564–1616) wrote the works traditionally ascribed to him. The Clinic achieved its primary objective of eliminating all other known candidates and thus confirming that Shakespeare wrote them. Two general methods of analysis were applied to whole plays and variable-sized large texts: Discrete Composite Analysis and Continuous Composite Analysis.. The first uses univariate analysis to determine acceptance or rejection of forty-eight stylometric tests for each text. The second uses a multi-dimensional composite mean for Shakespeare derived from all forty-eight in order to determine acceptance or rejection for each text. This article notes the omission of Discrete Analysis to take into consideration statistical dependencies between the forty-eight tests, the partly arbitrary ‘handfitting’ of acceptance–rejection boundaries for each of the forty-eight tests, the failure to take into full account the factor of chronology, and the absence of discussion of the part played by prior probabilities as to existing beliefs concerning attribution. By this last point, I mean the role played by the existing traditional consensus as to Shakespeare attribution, prior to linguistic analysis. For Continuous Analysis, it is noted that the stated probabilities are not true probabilities as acknowledged, and that the resulting acceptance–rejection levels for them are calibrated in line with prior beliefs. Principal component analysis is shown to give improved results in dealing with co-authored Shakespeare plays, Henry VIII, Timon of Athens, and Pericles. This does not invalidate the overall aim of the Shakespeare Clinic.


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