An experimental comparison between rival theories of rapid automatized naming performance and its relationship to reading

Two studies investigated the degree to which the relationship between rapid automatized naming (RAN) performance and reading development is driven by shared phonological processes. Study 1 assessed RAN, phonological awareness, and reading performance in 1010 7- to -10 year-olds. Results showed that RAN deficits occurred in the absence of phonological awareness deficits. These were accompanied by modest reading delays. In structural equation modeling, solutions where RAN was subsumed within a phonological processing factor did not provide a good fit to the data, suggesting that processes outside phonology may drive RAN performance and its association with reading. Study 2 investigated Kail’s proposal that speed of processing underlies this relationship. Children with single RAN deficits showed slower speed of processing than did closely matched controls performing normally on RAN. However, regression analysis revealed that RAN made a unique contribution to reading even after accounting for processing speed. Theoretical implications are discussed.

An examination of the complementary volume–volatility information theories

The volume–volatility relationship during the dissemination stages of information flow is examined by analyzing various theories relating volume and volatility as complementary rather than competing models. The mixture of distributions hypothesis, sequential arrival of information hypothesis, the dispersion of beliefs hypothesis, and the noise trader hypothesis all add to the understanding of how volume and volatility interact for different types of futures traders. An integrated picture of the volume–volatility relationship is provided by investigating the dynamic linear and nonlinear associations between volatility and the volume of informed (institutional) and uninformed (the general public) traders. In particular, the trading behavior explanation for the persistence of futures volatility, the effect of the timing of private information arrival, and the response of institutional traders to excess noise trading risk is examined

Considering the normative, systemic and procedural dimensions in indicator-based sustainability assessments in agriculture

This paper develops a framework for evaluating sustainability assessment methods by separately analyzing their normative, systemic and procedural dimensions as suggested by Wiek and Binder [Wiek, A, Binder, C. Solution spaces for decision-making – a sustainability assessment tool for city-regions. Environ Impact Asses Rev 2005, 25: 589-608.]. The framework is then used to characterize indicator-based sustainability assessment methods in agriculture. For a long time, sustainability assessment in agriculture has focused mostly on environmental and technical issues, thus neglecting the economic and, above all, the social aspects of sustainability, the multifunctionality of agriculture and the applicability of the results. In response to these shortcomings, several integrative sustainability assessment methods have been developed for the agricultural sector. This paper reviews seven of these that represent the diversity of tools developed in this area. The reviewed assessment methods can be categorized into three types: (i) top-down farm assessment methods; (ii) top-down regional assessment methods with some stakeholder participation; (iii) bottom-up, integrated participatory or transdisciplinary methods with stakeholder participation throughout the process. The results readily show the trade-offs encountered when selecting an assessment method. A clear, standardized, top-down procedure allows for potentially benchmarking and comparing results across regions and sites. However, this comes at the cost of system specificity. As the top-down methods often have low stakeholder involvement, the application and implementation of the results might be difficult. Our analysis suggests that to include the aspects mentioned above in agricultural sustainability assessment, the bottomup, integrated participatory or transdisciplinary methods are the most suitable ones.

Normative, systemic and procedural aspects: a review of indicator‐based sustainability assessments in agriculture

Several methods for assessing the sustainability of agricultural systems have been developed. These methods do not fully: (i) take into account the multi‐functionality of agriculture; (ii) include multidimensionality; (iii) utilize and implement the assessment knowledge; and (iv) identify conflicting goals and trade‐offs. This paper reviews seven recently developed multidisciplinary indicator‐based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis, (3) a reproducible structure of the approach. The approaches can be categorized into three typologies. The top‐down farm assessments focus on field or farm assessment. They have a clear procedure for measuring the indicators and assessing the sustainability of the system, which allows for benchmarking across farms. The degree of participation is low, potentially affecting the implementation of the results negatively. The top‐down regional assessment assesses the on‐farm and the regional effects. They include some participation to increase acceptance of the results. However, they miss the analysis of potential trade‐offs. The bottom‐up, integrated participatory or transdisciplinary approaches focus on a regional scale. Stakeholders are included throughout the whole process assuring the acceptance of the results and increasing the probability of implementation of developed measures. As they include the interaction between the indicators in their system representation, they allow for performing a trade‐off analysis. The bottom‐up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.