Accountability and the making of knowledge statements : a study of academic discourse

This study investigates the manifestation of speaker accountability in connection with knowledge statements in two different kinds of academic discourse. The study focuses on knowledge statements which feature a set of knowledge stating verbs, namely argue, claim, suggest, propose, maintain, assume and believe. A corpus is used as the empirical basis and a general metadiscursive approach primarily informed by ideas from a recent account of metadiscourse (Hyland 2005a) is adopted (combined with reasoning from dialogic frameworks, e.g. Todorov 1984, Bakhtin 1999). The study falls into four parts: First, the study establishes what it is in the utterance that affects the manifestation of speaker accountability in connection with knowledge statements; speaker accountability is associated with how vocally present or absent speakers are in their texts at the particular point of the knowledge statement, i.e. as connected to the concept of discourse voice. Discourse voice maps directly onto a scalar conception of accountability and a model describing this interactive relationship is proposed. Second, the study investigates differences between the knowledge stating verbs selected with respect to their occurrence in typical accountability contexts (i.e. contexts in which speakers are accountable to different degrees). The result of the corpus investigation indicates that the verbs investigated display significant differences in terms of typical accountability contexts. For example, believe is found to be a typical High accountability verb whereas claim is typically found in Low accountability contexts and suggest occurs as a typical Medium-to-High accountability verb. Third, the study also investigates potential differences in the typical accountability contexts of the knowledge stating verbs across two different academic disciplines. The corpus is divided into two sub-corpora, one part featuring texts from two linguistic journals and the other part featuring texts from two journals of literary theory and literary history. The outcome of the investigation is that there are few significant differences across the two sub-corpora. Knowledge stating verbs appear to occur in similar kinds of accountability contexts in linguistic and in literary texts. Finally, the study addresses the issue of what accountability is, i.e. its status in a theory of language. It is established that accountability can be explained by appeal to social knowledge. Such social knowledge is addressed at the level of metadiscourse in communication. The discussion leads to the proposal of a layered concept of metadiscourse where accountability is claimed to be directly associated with higher-level metadiscourse

Coherence in natural language : data structures and applications

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, February 2005.Includes bibliographical references (leaves [143]-148).(cont.) baseline, and that some coherence-based approaches best predict the human data. However, coherence-based algorithms that operate on trees did not perform as well as coherence-based algorithms that operate on more general graphs. It is suggested that that might in part be due to the fact that more general graphs are more descriptively adequate than trees for representing discourse coherence.The general topic of this thesis is coherence in natural language, where coherence refers to informational relations that hold between segments of a discourse. More specifically, this thesis aims to (1) develop criteria for a descriptively adequate data structure for representing discourse coherence; (2) test the influence of coherence on psycholinguistic processes, in particular, pronoun processing; (3) test the influence of coherence on the relative saliency of discourse segments in a text. In order to address the first aim, a method was developed for hand-annotating a database of naturally occurring texts for coherence structures. The thus obtained database of coherence structures was used to test assumptions about descriptively adequate data structures for representing discourse coherence. In particular, the assumption that discourse coherence can be represented in trees was tested, and results suggest that more powerful data structures than trees are needed (labeled chain graphs, where the labels represent types of coherence relations, and an ordered array of nodes represents the temporal order of discourse segments in a text). The second aim was addressed in an on-line comprehension and an off-line production experiment. Results from both experiments suggest that only a coherence-based account predicted the full range of observed data. In that account, the observed preferences in pronoun processing are not a result of pronoun-specific mechanisms, but a byproduct of more general cognitive mechanisms that operate when establishing coherence. In order to address the third aim, layout-, word-, and coherence-based approaches to discourse segment ranking were compared to human rankings. Results suggest that word-based accounts provide a strongby Florian Wolf.Ph.D