This is it ! : Indicating and looking in collaborative work at distance

Little is known of the interplay between deixis and eye movements in remote collaboration. This paper presents quantitative results from an experiment where participant pairs had to collaborate at a distance using chat tools that differed in the way messages could be enriched with spatial information from the map in the shared workspace. We studied how the availability of what we defined as an Explicit Referencing mechanism (ER) affected the coordination of the eye movements of the participants. The manipulation of the availability of ER did not produce any significant difference on the gaze coupling. However, we found a primary relation between the pairs recurrence of eye movements and their task performance. Implications for design are discussed

Annotations of maps in collaborative work at a distance

This thesis inquires how map annotations can be used to sustain remote collaboration. Maps condense the interplay of space and communication, solving linguistic references by linking conversational content to the actual places to which it refers. This is a mechanism people are accustomed to. When we are face-to-face, we can point to things around us. However, at a distance, we need to recreate a context that can help disambiguate what we mean. A map can help recreate this context. However other technological solutions are required to allow deictic gestures over a shared map when collaborators are not co-located. This mechanism is here termed Explicit Referencing. Several systems that allow sharing maps annotations are reviewed critically. A taxonomy is then proposed to compare their features. Two filed experiments were conducted to investigate the production of collaborative annotations of maps with mobile devices, looking for the reasons why people might want to produce these notes and how they might do so. Both studies led to very disappointing results. The reasons for this failure are attributed to the lack of a critical mass of users (social network), the lack of useful content, and limited social awareness. More importantly, the study identified a compelling effect of the way messages were organized in the tested application, which caused participants to refrain from engaging in content-driven explorations and synchronous discussions. This last qualitative observation was refined in a controlled experiment where remote participants had to solve a problem collaboratively, using chat tools that differed in the way a user could relate an utterance to a shared map. Results indicated that team performance is improved by the Explicit Referencing mechanisms. However, when this is implemented in a way that is detrimental to the linearity of the conversation, resulting in the visual dispersion or scattering of messages, its use has negative consequences for collaborative work at a distance. Additionally, an analysis of the eye movements of the participants over the map helped to ascertain the interplay of deixis and gaze in collaboration. A primary relation was found between the pair's recurrence of eye movements and their task performance. Finally, this thesis presents an algorithm that detects misunderstandings in collaborative work at a distance. It analyses the movements of collaborators' eyes over the shared map, their utterances containing references to this workspace, and the availability of "remote" deictic gestures. The algorithm associates the distance between the gazes of the emitter and gazes of the receiver of a message with the probability that the recipient did not understand the message

How journal rankings can suppress interdisciplinary research. A comparison between Innovation Studies and Business & Management

This study provides quantitative evidence on how the use of journal rankings can disadvantage interdisciplinary research in research evaluations. Using publication and citation data, it compares the degree of interdisciplinarity and the research performance of a number of Innovation Studies units with that of leading Business & Management schools in the UK. On the basis of various mappings and metrics, this study shows that: (i) Innovation Studies units are consistently more interdisciplinary in their research than Business & Management schools; (ii) the top journals in the Association of Business Schools' rankings span a less diverse set of disciplines than lower-ranked journals; (iii) this results in a more favourable assessment of the performance of Business & Management schools, which are more disciplinary-focused. This citation-based analysis challenges the journal ranking-based assessment. In short, the investigation illustrates how ostensibly 'excellence-based' journal rankings exhibit a systematic bias in favour of mono-disciplinary research. The paper concludes with a discussion of implications of these phenomena, in particular how the bias is likely to affect negatively the evaluation and associated financial resourcing of interdisciplinary research organisations, and may result in researchers becoming more compliant with disciplinary authority over time.Comment: 41 pages, 10 figure

Marking as judgment

An aspect of assessment which has received little attention compared with perennial concerns, such as standards or reliability, is the role of judgment in marking. This paper explores marking as an act of judgment, paying particular attention to the nature of judgment and the processes involved. It brings together studies which have explored marking from a psychological perspective for the purpose of critical discussion of the light they shed on each other and on the practice of marking. Later stages speculate on recent developments in psychology and neuroscience which may cast further light on educational assessment

How Journal Rankings can suppress Interdisciplinary Research – A Comparison between Innovation Studies and Business & Management

This study provides new quantitative evidence on how journal rankings can disadvantage interdisciplinary research during research evaluations. Using publication data, it compares the degree of interdisciplinarity and the research performance of innovation studies units with business and management schools in the UK. Using various mappings and metrics, this study shows that: (i) innovation studies units are consistently more interdisciplinary than business and management schools; (ii) the top journals in the Association of Business Schools’ rankings span a less diverse set of disciplines than lower ranked journals; (iii) this pattern results in a more favourable performance assessment of the business and management schools, which are more disciplinary-focused. Lastly, it demonstrates how a citation-based analysis challenges the ranking-based assessment. In summary, the investigation illustrates how ostensibly ‘excellence-based’ journal rankings have a systematic bias in favour of mono-disciplinary research. The paper concludes with a discussion of implications of these phenomena, in particular how resulting bias is likely to affect negatively the evaluation and associated financial resourcing of interdisciplinary organisations, and may encourage researchers to be more compliant with disciplinary authority.Interdisciplinary, Evaluation, Ranking, Innovation, Bibliometrics, REF

Building capacity in climate change policy analysis and negotiation: methods and technologies

Capacity building is often cited as the reason “we cannot just pour money into developing countries” and why so many development projects fail because their design does not address local conditions. It is therefore a key technical and political concept in international development. Some of the poorest countries in the world are also some of the most vulnerable to the impacts of climate change. Their vulnerability is in part due to a lack of capacity to plan and anticipate the effects of climate change on crops, water resources, urban electricity demand etc. What capacities do these countries lack to deal with climate change? How will they cope? What steps can they take to reduce their vulnerability? This innovative and high-profile research project was part of a larger project (called C3D) and conducted with non-governmental organisations in Senegal, South Africa and Sri Lanka. The research involved several participatory workshops and a questionnaire to all three research centres

Revisiting Absolute Pose Regression

Images provide direct evidence for the position and orientation of the camera in space, known as camera pose. Traditionally, the problem of estimating the camera pose requires reference data for determining image correspondence and leveraging geometric relationships between features in the image. Recent advances in deep learning have led to a new class of methods that regress the pose directly from a single image. This thesis proposes methods for absolute camera pose regression. Absolute pose regression estimates the pose of a camera from a single image as the output of a fixed computation pipeline. These methods have many practical benefits over traditional methods, such as constant inference speed and simplicity of use. However, they also have severe limitations, the most significant of which are high pose error and the fact that a network must be trained for each new scene. Despite the negatives, absolute pose regression is an exciting line of research with many potential use cases. Our work focuses on three areas. First, we investigate the use of absolute pose regression across multiple scenes. We propose a method for using a mostly shared network to perform pose regression across multiple scenes without significant increase in pose error relative to per-scene networks. With this approach, we also show how the features learned during multi-scene training do not transfer to pose regression in new scenes. Next, we propose a new convolutional network to improve the accuracy of absolute pose regression. The new network takes inspiration from traditional methods to design a network explicitly for camera pose regression. As opposed to the black box approaches used by other methods, out method results in a significant decrease in pose error. Finally, we show an application of the new method to share network weights to estimate camera pose in multiple scenes. Due to the more explicit design of the network, it is naturally partitioned into scene-dependent and scene-agnostic layers, allowing us to transfer pretrained weights to novel scenes without needing to retrained the entire network. The contribution of this thesis is a novel architecture for absolute pose regression which directly uses well known geometric relations that results in higher pose accuracy and allows for localization within novel scenes without needing to retrain the full network

STEPS Centre research: our approach to impact

The ‘impact’ of research has seen a dramatic rise up the UK’s policy agenda in recent years. But what does ‘impact’ really mean? How do researchers and others respond to the new ‘impact agenda’ and how might we best plan, monitor and report on impact? This working paper attempts to provide answers to some of these questions by reviewing various understandings of ‘impact’ and describing the approach used by the ESRC STEPS Centre in its second five-year phase of funding. In particular, we draw on our experience of adapting and employing a down-scaled version of ‘participatory impact pathways analysis’ (PIPA) and reflect on its utility and potential as a tool for planning relatively small-scale social science/ interdisciplinary research projects conducted with partners in developing countries. In using PIPA, the STEPS Centre has adapted the idea of ‘impact pathways’ in line with its broader ‘pathways approach’, which focusses on complex and dynamic interactions between knowledge, politics and ‘social, technological and environmental pathways to sustainability’. In this way, PIPA has been useful in articulating and exploring the potential impact of STEPS Centre projects: it has helped to map out the networks known to the researchers, appreciate different perspectives held by the team members and generate an understanding of the narratives, networks and policy processes under study. Although the possibility for detailed ex ante prediction of impact pathways is limited, using PIPA has helped teams to be ready to maximise communication and engagement opportunities, and to link research across different STEPS Centre projects and beyond. The working paper also describes how PIPA may be used iteratively in a way that enables reflexive learning amongst research teams. Lastly, we speculate on the ways in which PIPA may be further developed and used in ex post impact monitoring and evaluation into the future