title: Rigour and rigour mortis? Planning, calculative rationality, and forces of stability and change

authors: White, Iain

subjects: Science & Technology

abstract: A defining feature of planning is that it is informed by sound evidence. An ever more diverse range of decision support tools is available to help achieve this, a trend that is set to accelerate along with the rise of Big Data and Smart Cities. At the same time, planning is frequently requested to improve the urban and environmental outcomes it helps deliver. This research draws upon intellectual resources from Science and Technology Studies, and empirical data from actors across the science–policy–practice interface, to analyse critically issues connected to the design, application and wider effects of calculative practices within planning. It finds that these practices selectively open up or foreclose discourses and play important political roles relating to ordering complexity and mitigating professional risk. They are also revealed as underpinning a stability and certainty within decision making that not only maintains the power of established calculative agencies but also serves to replicate an ideology of urban form that is in tension with more normative calls for change. More broadly, the findings help unsettle the planner and planning policy as the key agent able to change planning outcomes, which is instead revealed as more contingent on the political, institutional and professional culture, and the ways human and non-human objects align and combine to create internal stability when there are external calls for change.

text: Rigour and rigour mortis? Planning, calculative rationality, and forces of stability and change A defining feature of planning is that it is informed by sound evidence. An ever more diverse range of decision support tools is available to help achieve this, a trend that is set to accelerate along with the rise of Big Data and Smart Cities. At the same time, planning is frequently requested to improve the urban and environmental outcomes it helps deliver. This research draws upon intellectual resources from Science and Technology Studies, and empirical data from actors across the science–policy–practice interface, to analyse critically issues connected to the design, application and wider effects of calculative practices within planning. It finds that these practices selectively open up or foreclose discourses and play important political roles relating to ordering complexity and mitigating professional risk. They are also revealed as underpinning a stability and certainty within decision making that not only maintains the power of established calculative agencies but also serves to replicate an ideology of urban form that is in tension with more normative calls for change. More broadly, the findings help unsettle the planner and planning policy as the key agent able to change planning outcomes, which is instead revealed as more contingent on the political, institutional and professional culture, and the ways human and non-human objects align and combine to create internal stability when there are external calls for change.

year: 2019

title: Concept-based Text Clustering

authors: Huang, Lan

subjects: clustering

abstract: Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

text: Concept-based Text Clustering Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

year: 2011

title: An evaluation of Te Rau Puawai workforce 100: Te Rau Puawai support team and staff perspectives

authors: Nikora, Linda Waimarie

subjects: Maori students

abstract: To evaluate the Te Rau Puawai programme, the Ministry of Health commissioned the
Maori and Psychology Research Unit of the University of Waikato in July 2001. The
overall aim of the evaluation was to provide the Ministry with a clearer understanding
of the programme including: the perceived critical success factors, the barriers if any
regarding Te Rau Puawai, the impact of the programme, the extent to which the
programme may be transferable, gaps in the programme, and suggested
improvements.
The Te Rau Puawai support team were identified as an important source of support
for bursars particularly the support provided by the coordinator and administrator.
This report documents the perspectives of four members of the telephone support
team (including the coordinator), and individual interviews held with the coordinator
and the administrator in addressing the objectives of the evaluation.

text: An evaluation of Te Rau Puawai workforce 100: Te Rau Puawai support team and staff perspectives To evaluate the Te Rau Puawai programme, the Ministry of Health commissioned the
Maori and Psychology Research Unit of the University of Waikato in July 2001. The
overall aim of the evaluation was to provide the Ministry with a clearer understanding
of the programme including: the perceived critical success factors, the barriers if any
regarding Te Rau Puawai, the impact of the programme, the extent to which the
programme may be transferable, gaps in the programme, and suggested
improvements.
The Te Rau Puawai support team were identified as an important source of support
for bursars particularly the support provided by the coordinator and administrator.
This report documents the perspectives of four members of the telephone support
team (including the coordinator), and individual interviews held with the coordinator
and the administrator in addressing the objectives of the evaluation.

year: 2002-05-01