The Borrowers: Researching the cognitive aspects of translation

The paper considers the interdisciplinary interaction of research on the cognitive aspects of translation. Examples of influence from linguistics, psychology, neuroscience, cognitive science, reading and writing research and language technology are given, with examples from specific sub-disciplines within each one. The breadth of borrowing by researchers in cognitive translatology is made apparent, but the minimal influence of cognitive translatology on the respective disciplines themselves is also highlighted. Suggestions for future developments are made, including ways in which the domain of cognitive translatology might exert greater influence on other disciplines

Origins of Modern Data Analysis Linked to the Beginnings and Early Development of Computer Science and Information Engineering

The history of data analysis that is addressed here is underpinned by two themes, -- those of tabular data analysis, and the analysis of collected heterogeneous data. "Exploratory data analysis" is taken as the heuristic approach that begins with data and information and seeks underlying explanation for what is observed or measured. I also cover some of the evolving context of research and applications, including scholarly publishing, technology transfer and the economic relationship of the university to society.Comment: 26 page

Undesirable biases in NLP: Averting a crisis of measurement

As Natural Language Processing (NLP) technology rapidly develops and spreads into daily life, it becomes crucial to anticipate how its use could harm people. However, our ways of assessing the biases of NLP models have not kept up. While especially the detection of English gender bias in such models has enjoyed increasing research attention, many of the measures face serious problems, as it is often unclear what they actually measure and how much they are subject to measurement error. In this paper, we provide an interdisciplinary approach to discussing the issue of NLP model bias by adopting the lens of psychometrics -- a field specialized in the measurement of concepts like bias that are not directly observable. We pair an introduction of relevant psychometric concepts with a discussion of how they could be used to evaluate and improve bias measures. We also argue that adopting psychometric vocabulary and methodology can make NLP bias research more efficient and transparent

The Noetic Prism

Definitions of ‘knowledge’ and its relationships with ‘data’ and ‘information’ are varied, inconsistent and often contradictory. In particular the traditional hierarchy of data-information-knowledge and its various revisions do not stand up to close scrutiny. We suggest that the problem lies in a flawed analysis that sees data, information and knowledge as separable concepts that are transformed into one another through processing. We propose instead that we can describe collectively all of the materials of computation as ‘noetica’, and that the terms data, information and knowledge can be reconceptualised as late-binding, purpose-determined aspects of the same body of material. Changes in complexity of noetica occur due to value-adding through the imposition of three different principles: increase in aggregation (granularity), increase in set relatedness (shape), and increase in contextualisation through the formation of networks (scope). We present a new model in which granularity, shape and scope are seen as the three vertices of a triangular prism, and show that all value-adding through computation can be seen as movement within the prism space. We show how the conceptual framework of the noetic prism provides a new and comprehensive analysis of the foundations of computing and information systems, and how it can provide a fresh analysis of many of the common problems in the management of intellectual resources