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Words originating from shortening, including acronyms and clippings, constitute a treasure trove of insight into phonological grammar. In particular, they serve as an ideal testing ground for Optimality Theory (OT) and its view of grammar as an interaction of markedness constraints, which express (dis-) preferences regarding phonological structure in output forms, and faithfulness constraints, which require output forms to correspond to input structure (Prince and Smolensky 1993). This is because shortenings are characterised by a sharply diminished role of faithfulness, allowing for markedness constraints to make their force felt (“The Emergence of the Unmarked”). This article aims to demonstrate the heuristic value of shortening data for testing the OT model and for shedding light on various controversies in German phonology. A particular concern is to draw attention to the need for properly sorting the shortening data, to identify influences on phonological structure due to internal domain boundaries or to special correspondence effects potentially obscuring the view on the maximally unmarked patterns.
Notions such as “corpus-driven” versus “theory-driven” bring into focus the specific role of corpora in linguistic research. As for phonology with its intrinsic focus on abstract categorical representation, there is a question of how a strictly corpus-driven approach can yield insight into relevant structures. Here we argue for a more theory-driven approach to phonology based on the concept of a phonological grammar in terms of interacting constraints. Empirical validation of such grammars comes from the potential convergence of the evidence from various sources including typological data, neutralization patterns, and in particular patterns observed in the creative use of language such as acronym formation, loanword adaptation, poetry, and speech errors. Further empirical validation concerns specific predictions regarding phonetic differences among opposition members, paradigm uniformity effects, and phonetic implementation in given segmental and prosodic contexts. Corpora in the narrowest sense (i.e. “raw” data consisting of spontaneous speech produced in natural settings) are useful for testing these predictions, but even here, special purpose-built corpora are often necessary.