Rigidity : a cognitive style conceptualization of depression : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Psychology at Massey University

The traditional ideas of depression as an affective illness are examined and evidence is presented that contrary to the view presented in many texts, depression is also associated with thought disorders as severe as those experienced in other psychopathological illnesses. A model of depression as a single entity is proposed that suggests that the various manifestations of the disorder are due to a single underlying mechanism. This mechanism is conceived of in terms of cognitive style and cognitive control theory and evidence is presented that this is an adaptive mechanism for the individual and consists of selective blocking of incoming stimuli or in more general terms, 'rigidity'. Twelve depressed patients were examined using a battery of tests which yielded 22 measures including level of depression, rigidity, anxiety, field-dependence and various scales of personality. These measures were then correlated using Pearsons Product-Moment correlation coefficients and were then subjected to cluster analysis using Tryons modification of Holzinger and Harmon's B-coefficient technique. This gave four meaningful clusters of which three matched the components of Becks primary triad, with the important addition that this analysis reveals the importance of rigidity as a factor in Beck's second component-negative self-concept

Towards Maximising Openness in Digital Sensitivity Review using Reviewing Time Predictions

The adoption of born-digital documents, such as email, by governments, such as in the UK and USA, has resulted in a large backlog of born-digital documents that must be sensitivity reviewed before they can be opened to the public, to ensure that no sensitive information is released, e.g. personal or confidential information. However, it is not practical to review all of the backlog with the available reviewing resources and, therefore, there is a need for automatic techniques to increase the number of documents that can be opened within a fixed reviewing time budget. In this paper, we conduct a user study and use the log data to build models to predict reviewing times for an average sensitivity reviewer. Moreover, we show that using our reviewing time predictions to select the order that documents are reviewed can markedly increase the ratio of reviewed documents that are released to the public, e.g. +30% for collections with high levels of sensitivity, compared to reviewing by shortest document first. This, in turn, increases the total number of documents that are opened to the public within a fixed reviewing time budget, e.g. an extra 200 documents in 100 hours reviewing

Active Learning Strategies for Technology Assisted Sensitivity Review

Government documents must be reviewed to identify and protect any sensitive information, such as personal information, before the documents can be released to the public. However, in the era of digital government documents, such as e-mail, traditional sensitivity review procedures are no longer practical, for example due to the volume of documents to be reviewed. Therefore, there is a need for new technology assisted review protocols to integrate automatic sensitivity classification into the sensitivity review process. Moreover, to effectively assist sensitivity review, such assistive technologies must incorporate reviewer feedback to enable sensitivity classifiers to quickly learn and adapt to the sensitivities within a collection, when the types of sensitivity are not known a priori. In this work, we present a thorough evaluation of active learning strategies for sensitivity review. Moreover, we present an active learning strategy that integrates reviewer feedback, from sensitive text annotations, to identify features of sensitivity that enable us to learn an effective sensitivity classifier (0.7 Balanced Accuracy) using significantly less reviewer effort, according to the sign test (p < 0.01 ). Moreover, this approach results in a 51% reduction in the number of documents required to be reviewed to achieve the same level of classification accuracy, compared to when the approach is deployed without annotation features

A design pattern for responsible information systems education

This paper explores the idea of responsible systems design. To do so, it examines a case study - the accreditation of Information Systems (IS) courses by the professional body. A professionally accredited educational program, like any other non-trivial design product, represents the balancing of competing influences, ideas and stakeholders. The case is particularly relevant because there have been significant changes in the context of Australian IS education recently that have made more complex the task of designing educational systems in a responsible manner. A general approach to addressing this complexity is articulated here as a design pattern to guide IS educational design. The pattern identifies the influences on design, the processes and products of design and the feedback mechanism required to demonstrate that stakeholder requirements are satisfied. Design tensions and principles arising from the model are discussed and future work identified<br /

Towards a classifier for digital sensitivity review

The sensitivity review of government records is essential before they can be released to the official government archives, to prevent sensitive information (such as personal information, or that which is prejudicial to international relations) from being released. As records are typically reviewed and released after a period of decades, sensitivity review practices are still based on paper records. The transition to digital records brings new challenges, e.g. increased volume of digital records, making current practices impractical to use. In this paper, we describe our current work towards developing a sensitivity review classifier that can identify and prioritise potentially sensitive digital records for review. Using a test collection built from government records with real sensitivities identified by government assessors, we show that considering the entities present in each record can markedly improve upon a text classification baseline

Information Systems Foundations - Karl Popper's Third World

The various information professions have matured separately over the years, developing different bodies of theory and practice to meet their evolving purposes and needs. A problem arises however, when different information professions address the same knowledge domain and there is no explicit correspondence between the conceptual structures embedded independently in each. In this situation, a knowledge worker involved in the domain is faced with a range of possibly incompatible structures presented in different forms by a range of information professions. This is a common problem that is being exacerbated by the explosion in information production and the widening access to information distribution technology, notably the World Wide Web. Information Systems now need to combine the best of what the information professions in a domain have to offer the domain’s knowledge workers. This paper examines the problem by exploring one of the foundations of the information disciplines - Karl Popper’s 3 Worlds theory, applying it to a case study and suggesting that the Information Systems discipline alone has a sufficiently broad agenda to integrate the various Informatics themes needed to support today’s knowledge workers