From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Actionable climate knowledge: From analysis to synthesis

The traditional reductionist approach to science has a tendency to create 'islands of knowledge in a sea of ignorance', with a much stronger focus on analysis of scientific inputs rather than synthesis of socially relevant outcomes. This might be the principal reason why intended end users of climate information generally fail to embrace what the climate science community has to offer. The translation of climate information into real-life action requires 3 essential components: salience (the perceived relevance of the information), credibility (the perceived technical quality of the information) and legitimacy (the perceived objectivity of the process by which the information is shared). We explore each of these components using 3 case studies focused on dryland cropping in Australia, India and Brazil. In regards to 'salience' we discuss the challenge for climate science to be 'policy-relevant', using Australian drought policy as an example. In a village in southern India 'credibility' was gained through engagement between scientists and risk managers with the aim of building social capital, achieved only at high cost to science institutions. Finally, in Brazil we found that 'legitimacy' is a fragile, yet renewable resource that needs to be part of the package for successful climate applications; legitimacy can be easily eroded but is difficult to recover. We conclude that climate risk management requires holistic solutions derived from cross-disciplinary and participatory, user-oriented research. Approaches that combine climate, agroecological and socioeconomic models provide the scientific capabilities for establishment of 'borderless' institutions without disciplinary constraints. Such institutions could provide the necessary support and flexibility to deliver the social benefits of climate science across diverse contexts. Our case studies show that this type of solution is already being applied, and suggest that the climate science community attempt to address existing institutional constraints, which still impede climate risk management.

A knowledge-based clustering scheme

In this paper the notion of conceptual cohesiveness is precised and used to group objects semantically, based on a knowledge structure called ‘cohesion forest’. A set of axioms is proposed which should be satisfied to make the generated clusters meaningful.

Assessing university students' prior knowledge

The aim of this dissertation was to explore how different types of prior knowledge influence student achievement and how different assessment methods influence the observed effect of prior knowledge. The project started by creating a model of prior knowledge which was tested in various science disciplines. Study I explored the contribution of different components of prior knowledge on student achievement in two different mathematics courses. The results showed that the procedural knowledge components which require higher-order cognitive skills predicted the final grades best and were also highly related to previous study success. The same pattern regarding the influence of prior knowledge was also seen in Study III which was a longitudinal study of the accumulation of prior knowledge in the context of pharmacy. The study analysed how prior knowledge from previous courses was related to student achievement in the target course. The results implied that students who possessed higher-level prior knowledge, that is, procedural knowledge, from previous courses also obtained higher grades in the more advanced target course. Study IV explored the impact of different types of prior knowledge on students’ readiness to drop out from the course, on the pace of completing the course and on the final grade. The study was conducted in the context of chemistry. The results revealed again that students who performed well in the procedural prior-knowledge tasks were also likely to complete the course in pre-scheduled time and get higher final grades. On the other hand, students whose performance was weak in the procedural prior-knowledge tasks were more likely to drop out or take a longer time to complete the course. Study II explored the issue of prior knowledge from another perspective. Study II aimed to analyse the interrelations between academic self-beliefs, prior knowledge and student achievement in the context of mathematics. The results revealed that prior knowledge was more predictive of student achievement than were other variables included in the study. Self-beliefs were also strongly related to student achievement, but the predictive power of prior knowledge overruled the influence of self-beliefs when they were included in the same model. There was also a strong correlation between academic self-beliefs and prior-knowledge performance. The results of all the four studies were consistent with each other indicating that the model of prior knowledge may be used as a potential tool for prior knowledge assessment. It is useful to make a distinction between different types of prior knowledge in assessment since the type of prior knowledge students possess appears to make a difference. The results implied that there indeed is variation between students’ prior knowledge and academic self-beliefs which influences student achievement. This should be taken into account in instruction.

Law of the Republic of Uzbekistan "On Protection of Mental Health in the Population of Uzbekistan"

The law provides rights for PWD for easy access of public goods, including education, social security, medical treatment, occupational and social rehabilitation and establishes an extent of responsibility of the government and its bodies for the creation of favourable conditions for the social adaptation of PWDs in market environment conditions.

Sustained genetic control of wheat rust diseases in north-eastern Australia

Control of wheat rusts in north-eastern Australia has been based on resistance breeding since the early 1920s. It has been an enduring journey of discovery, disappointment, and achievement, which has culminated in a pool of knowledge and expertise upon which today's plant breeders can efficiently target durable resistance to the major rust diseases. This paper outlines significant advances in genetic control of rusts in the region, with particular emphasis on the invaluable role played by the University of Sydney rust control program and its influence on wheat breeding in the region and throughout Australia. This paper is part of ‘Global Landscapes in Cereal Rust Control’, see Aust. J. Agric. Res. Vol. 58, no. 6.

Supervisors' emerging role in second-generation knowledge management

This study examines supervisors' emerging new role in a technical customer service and home customers division of a large Finnish telecommunications corporation. Data of the study comes from a second-generation knowledge management project, an intervention research, which was conducted for supervisors of the division. The study exemplifies how supervision work is transforming in high technology organization characterized with high speed of change in technologies, products, and in grass root work practices. The intervention research was conducted in the division during spring 2000. Primary analyzed data consists of six two-hour videorecorded intervention sessions. Unit of analysis has been collective learningactions. Researcher has first written conversation transcripts out of the video-recorded meetings and then analyzed this qualitative data using analytical schema based on collective learning actions. Supervisors' role is conceptualized as an actor of a collective and dynamic activity system, based on the ideas from cultural historical activity theory. On knowledge management researcher has takena second-generation knowledge management viewpoint, following ideas fromcultural historical activity theory and developmental work research. Second-generation knowledge management considers knowledge embedded and constructed in collective practices, such as innovation networks or communities of practice (supervisors' work community), which have the capacity to create new knowledge. Analysis and illustration of supervisors' emerging new role is conceptualized in this framework using methodological ideas derived from activity theory and developmental work research. Major findings of the study show that supervisors' emerging new role in a high technology telecommunication organization characterized with high speed of discontinuous change in technologies, products, and in grass-root practices cannot be defined or characterized using a normative management role/model. Their role is expanding two-dimensionally, (1) socially and (2) in new knowledge, and work practices. The expansion in organization and inter-organizational network (social expansion) causes pressures to manage a network of co-operation partners and subordinates. On the other hand, the faster speed of change in technological solutions, new products, and novel customer wants (expansion in knowledge) causes pressures for supervisors to innovate quickly new work practices to manage this change. Keywords: Activity theory, knowledge management, developmental work research, supervisors, high technology organizations, telecommunication organizations, second-generation knowledge management, competence laboratory, intervention research, learning actions.