In “A Robust Transformation Procedure,” Martin and Vanberg (2007, hereafter MV) propose a new method for rescaling the raw virgin text scores produced by the “Wordscores” procedure of Laver, Benoit, and Garry (2003, hereafter LBG). Their alternative method addresses two deficiencies they argue exist with the transformation of virgin text scores proposed by LBG: First, that the LBG transformation is sensitive to the selection of virgin texts, and second, that it distorts the reference metric by failing to recover the original reference scores when reference texts are scored and transformed as if they were virgin texts. Their proposed alternative is “robust” in the sense that it avoids both shortcomings. Not only is MV's transformation a welcome contribution to the Wordscores project but also the critical analysis on which it is based brings to light a number of assumptions and choices that face the analyst seeking to estimate actors' policy positions using statistical analyses of the texts they generate. When first describing the possibility of rescaling the raw virgin text estimates, we emphasized that our
particular approach to rescaling is not fundamental to our word-scoring technique but, rather, is a matter of substantive research design unrelated to the validity of the raw virgin text scores… Other transformations are of course possible. (LBG, 316)
To explore more fully into the assumptions and choices behind alternative transformations and the research designs which motivate them, we offer the following comments.