Children’s rights in India : parents’ and teachers’ attitudes, knowledge and perceptions

Individuals’ attitudes influence their behaviour towards children, including whether children’s rights and welfare are promoted. The attitudes generally present in a society shape a culture of how children are perceived and treated. This study explored the attitudes and knowledge of 300 Indian parents and teachers regarding children’s rights, and their perceptions about whether selected rights were secured in reality. Findings revealed that most parents and teachers had positive attitudes about children’s rights, including rights to health and education, and freedom from child marriage and inappropriate work. Yet, about one quarter of participants did not think children should have the rights to freedom of expression and association. Knowledge of laws promoting children’s rights was poor. Most parents and teachers perceived a denial of seven key rights in Indian children’s lived experience. Overall, fijindings suggest a need to heighten awareness of children’s rights and needs, which can improve attitudes towards the treatment of children. Effforts to heighten awareness and attitudes towards children’s rights are needed across society and in key sectors to enhance children’s lived experience.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Postpositivist research in education : theorising social structure in critical and institutional ethnography

This chapter charts the theories and methods being adopted in an investigation of the 'micro-politics' of teacher education policy reception at a site of higher education in Queensland from 1980 to 1990. The paper combines insights and methods from critical ethnography with those from the institutional ethnography of feminist sociologist Dorothy Smith to link local policy activity at the institutional site to broader social structures and processes. In this way, enquiry begins with--and takes into account--the experiences of those groups normally excluded from mainstream and even critical policy analysis.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Visualising mathematical knowledge and understanding

Contemporary mathematics education attempts to instil within learners the conceptualization of mathematics as a highly organized and inter-connected set of ideas. To support this, a means to graphically represent this organization of ideas is presented which reflects the cognitive mechanisms that shape a learner’s understanding. This organisation of information may then be analysed, with the view to informing the design of mathematics instruction in face-to-face and/or computer-mediated learning environments. However, this analysis requires significant work to develop both theory and practice.

Proteomics science & society : the role of knowledge translation in moving towards clinical applications

Background: Outside the mass-spectrometer, proteomics research does not take place in a vacuum. It is affected by policies on funding and research infrastructure. Proteomics research both impacts and is impacted by potential clinical applications. It provides new techniques & clinically relevant findings, but the possibilities for such innovations (and thus the perception of the potential for the field by funders) are also impacted by regulatory practices and the readiness of the health sector to incorporate proteomics-related tools & findings. Key to this process is how knowledge is translated. Methods: We present preliminary results from a multi-year social science project, funded by the Canadian Institutes of Health Research, on the processes and motivations for knowledge translation in the health sciences. The proteomics case within this wider study uses qualitative methods to examine the interplay between proteomics science and regulatory and policy makers regarding clinical applications of proteomics. Results: Adopting an interactive format to encourage conference attendees’ feedback, our poster focuses on deficits in effective knowledge translation strategies from the laboratory to policy, clinical, & regulatory arenas. An analysis of the interviews conducted to date suggests five significant choke points: the changing priorities of funding agencies; the complexity of proteomics research; the organisation of proteomics research; the relationship of proteomics to genomics and other omics sciences; and conflict over the appropriate role of standardisation. Conclusion: We suggest that engagement with aspects of knowledge translation, such as those mentioned above, is crucially important for the eventual clinical application ofproteomics science on any meaningful scale.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Maintaining a cognitive map in darkness : the need to fuse boundary knowledge with path integration

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

A framework for life cycle cost estimation of a product family at the early stage of product development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system.

Performance evaluation of onsite wastewater treatment : field sampling and preliminary evaluation of results

Background The onsite treatment of sewage and effluent disposal within the premises is widely prevalent in rural and urban fringe areas due to the general unavailability of reticulated wastewater collection systems. Despite the seemingly low technology of the systems, failure is common and in many cases leading to adverse public health and environmental consequences. Therefore it is important that careful consideration is given to the design and location of onsite sewage treatment systems. It requires an understanding of the factors that influence treatment performance. The use of subsurface effluent absorption systems is the most common form of effluent disposal for onsite sewage treatment and particularly for septic tanks. Additionally in the case of septic tanks, a subsurface disposal system is generally an integral component of the sewage treatment process. Therefore location specific factors will play a key role in this context. The project The primary aims of the research project are: • to relate treatment performance of onsite sewage treatment systems to soil conditions at site; • to identify important areas where there is currently a lack of relevant research knowledge and is in need of further investigation. These tasks were undertaken with the objective of facilitating the development of performance based planning and management strategies for onsite sewage treatment. The primary focus of the research project has been on septic tanks. Therefore by implication the investigation has been confined to subsurface soil absorption systems. The design and treatment processes taking place within the septic tank chamber itself did not form a part of the investigation. In the evaluation to be undertaken, the treatment performance of soil absorption systems will be related to the physico-chemical characteristics of the soil. Five broad categories of soil types have been considered for this purpose. The number of systems investigated was based on the proportionate area of urban development within the Brisbane region located on each soil types. In the initial phase of the investigation, though the majority of the systems evaluated were septic tanks, a small number of aerobic wastewater treatment systems (AWTS) were also included. This was primarily to compare the effluent quality of systems employing different generic treatment processes. It is important to note that the number of different types of systems investigated was relatively small. As such this does not permit a statistical analysis to be undertaken of the results obtained. This is an important issue considering the large number of parameters that can influence treatment performance and their wide variability. The report This report is the second in a series of three reports focussing on the performance evaluation of onsite treatment of sewage. The research project was initiated at the request of the Brisbane City Council. The work undertaken included site investigation and testing of sewage effluent and soil samples taken at distances of 1 and 3 m from the effluent disposal area. The project component discussed in the current report formed the basis for the more detailed investigation undertaken subsequently. The outcomes from the initial studies have been discussed, which enabled the identification of factors to be investigated further. Primarily, this report contains the results of the field monitoring program, the initial analysis undertaken and preliminary conclusions. Field study and outcomes Initially commencing with a list of 252 locations in 17 different suburbs, a total of 22 sites in 21 different locations were monitored. These sites were selected based on predetermined criteria. To obtain house owner agreement to participate in the monitoring study was not an easy task. Six of these sites had to be abandoned subsequently due to various reasons. The remaining sites included eight septic systems with subsurface effluent disposal and treating blackwater or combined black and greywater, two sites treating greywater only and six sites with AWTS. In addition to collecting effluent and soil samples from each site, a detailed field investigation including a series of house owner interviews were also undertaken. Significant observations were made during the field investigations. In addition to site specific observations, the general observations include the following: • Most house owners are unaware of the need for regular maintenance. Sludge removal has not been undertaken in any of the septic tanks monitored. Even in the case of aerated wastewater treatment systems, the regular inspections by the supplier is confined only to the treatment system and does not include the effluent disposal system. This is not a satisfactory situation as the investigations revealed. • In the case of separate greywater systems, only one site had a suitably functioning disposal arrangement. The general practice is to employ a garden hose to siphon the greywater for use in surface irrigation of the garden. • In most sites, the soil profile showed significant lateral percolation of effluent. As such, the flow of effluent to surface water bodies is a distinct possibility. • The need to investigate the subsurface condition to a depth greater than what is required for the standard percolation test was clearly evident. On occasion, seemingly permeable soil was found to have an underlying impermeable soil layer or vice versa. The important outcomes from the testing program include the following: • Though effluent treatment is influenced by the physico-chemical characteristics of the soil, it was not possible to distinguish between the treatment performance of different soil types. This leads to the hypothesis that effluent renovation is significantly influenced by the combination of various physico-chemical parameters rather than single parameters. This would make the processes involved strongly site specific. • Generally the improvement in effluent quality appears to take place only within the initial 1 m of travel and without any appreciable improvement thereafter. This relates only to the degree of improvement obtained and does not imply that this quality is satisfactory. This calls into question the value of adopting setback distances from sensitive water bodies. • Use of AWTS for sewage treatment may provide effluent of higher quality suitable for surface disposal. However on the whole, after a 1-3 m of travel through the subsurface, it was not possible to distinguish any significant differences in quality between those originating from septic tanks and AWTS. • In comparison with effluent quality from a conventional wastewater treatment plant, most systems were found to perform satisfactorily with regards to Total Nitrogen. The success rate was much lower in the case of faecal coliforms. However it is important to note that five of the systems exhibited problems with regards to effluent disposal, resulting in surface flow. This could lead to possible contamination of surface water courses. • The ratio of TDS to EC is about 0.42 whilst the optimum recommended value for use of treated effluent for irrigation should be about 0.64. This would mean a higher salt content in the effluent than what is advisable for use in irrigation. A consequence of this would be the accumulation of salts to a concentration harmful to crops or the landscape unless adequate leaching is present. These relatively high EC values are present even in the case of AWTS where surface irrigation of effluent is being undertaken. However it is important to note that this is not an artefact of the treatment process but rather an indication of the quality of the wastewater generated in the household. This clearly indicates the need for further research to evaluate the suitability of various soil types for the surface irrigation of effluent where the TDS/EC ratio is less than 0.64. • Effluent percolating through the subsurface absorption field may travel in the form of dilute pulses. As such the effluent will move through the soil profile forming fronts of elevated parameter levels. • The downward flow of effluent and leaching of the soil profile is evident in the case of podsolic, lithosol and kransozem soils. Lateral flow of effluent is evident in the case of prairie soils. Gleyed podsolic soils indicate poor drainage and ponding of effluent. In the current phase of the research project, a number of chemical indicators such as EC, pH and chloride concentration were employed as indicators to investigate the extent of effluent flow and to understand how soil renovates effluent. The soil profile, especially texture, structure and moisture regime was examined more in an engineering sense to determine the effect of movement of water into and through the soil. However it is not only the physical characteristics, but the chemical characteristics of the soil also play a key role in the effluent renovation process. Therefore in order to understand the complex processes taking place in a subsurface effluent disposal area, it is important that the identified influential parameters are evaluated using soil chemical concepts. Consequently the primary focus of the next phase of the research project will be to identify linkages between various important parameters. The research thus envisaged will help to develop robust criteria for evaluating the performance of subsurface disposal systems.

Observational research and verbal protocol methods

This paper describes observational research and verbal protocols methods, how these methods are applied and integrated within different contexts, and how they complement each other. The first case study focuses on nurses’ interaction during bandaging of patients’ lower legs. To maintain research rigor a triangulation approach was applied that links observations of current procedures, ‘talk-aloud’ protocol during interaction and retrospective protocol. Maps of interactions demonstrated that some nurses bandage more intuitively than others. Nurses who bandage intuitively assemble long sequences of bandaging actions while nurses who bandage less intuitively ‘focus-shift’ in between bandaging actions. Thus different levels of expertise have been identified. The second case study consists of two laboratory experiments. It focuses on analysing and comparing software and product design teams and how they approached a design problem. It is based on the observational and verbal data analysis. The coding scheme applied evolved during the analysis of the activity of each team and is identical for all teams. The structure of knowledge captured from the analysis of the design team maps of interaction is identified. The significance of this work is within its methodological approach. The maps of interaction are instrumental for understanding the activities and interactions of the people observed. By examining the maps of interaction, it is possible to draw conclusions about interactions, structure of knowledge captured and level of expertise. This research approach is transferable to other design domains. Designers will be able to transfer the interaction maps outcomes to systems and services they design.

Larger or broader : performance implications of size and diversity of the knowledge worker's egocentric network. [更多或更广：知识员工个人中心网络大小和 多样性对绩效的影响]

Management scholars and practitioners emphasize the importance of the size and diversity of a knowledge worker's social network. Constraints on knowledge workers’ time and energy suggest that more is not always better. Further, why and how larger networks contribute to valuable outcomes deserves further understanding. In this study, we offer hypotheses to shed insight on the question of the diminishing returns of large networks and the specific form of network diversity that may contribute to innovative performance among knowledge workers. We tested our hypotheses using data collected from 93 R&D engineers in a Sino-German automobile electronics company located in China. Study findings identified an inflection point, confirming our hypothesis that the size of the knowledge worker's egocentric network has an inverted U-shaped effect on job performance. We further demonstrate that network dispersion richness (the number of cohorts that the focal employee has connections to) rather than network dispersion evenness (equal distribution of ties across the cohorts) has more influence on the knowledge worker's job performance. Additionally, we found that the curvilinear effect of network size is fully mediated by network dispersion richness. Implications for future research on social networks in China and Western contexts are discussed.