Learning to make sense

Helsdingen, A. S., & Van den Bosch, K. (2009). Learning to make sense. Paper presented at the Cognitive Systems with Interactive sensors conference in Paris. November, 16-18, 2009, Paris, France.Sensemaking is the process of understanding situations of high complexity or uncertainty in order to make decisions. Individuals and teams that are good at sensemaking tend to collect and critically evaluate the available evidence, seek for consistency, and test assumptions underlying assessments. Furthermore, their experience allows them to have a high appreciation for how the context affects the problem. In this paper we will (1) present observations on successful and failing sensemaking in first responder teams, (2) discuss the development of sensemaking competency, and (3) present an approach for training the knowledge and skills that are critical for sensemaking

The Social Stratification of Social Risks: Class and Responsibility in the 'New' Welfare State

Welfare states are said to have evolved over the course of the past twenty years towards a ‘social investment’ model of welfare, characterised by a focus on equality of opportunity and upward social mobility combined with greater emphasis on individual responsibility. More or less concurrently, under the mantra of ‘individualisation’, scepticism has grown with regard to the relevance of traditional stratification schemes. This paper sets out to ascertain whether social class, i.e. intergenerational background, (still) affects the occurrence of ‘social risks’. Using SILC 2005 data, it considers the impact of social class (of origin) on a relevant selection of social risks: unemployment, ill-health, living in a jobless household, single parenthood, temporary employment, and low-paid employment. The results provide clear evidence of a continuing influence of social class. On this basis, we argue that a one-sided focus on individual responsibility could open the door to new forms of marginalisation.Ireland, Austerity, Fiscal Policy, Monetary Policy

A new poverty indicator for Europe:The extended headcount ratio

The methodology currently used to measure poverty in the European Union faces some important limitations. Capturing key aspects of poverty is done using a dashboard of indicators, which often tell conflicting stories. We propose a new income-based measure of poverty for Europe that captures in a consistent way in a single indicator the level of relative poverty, the intensity of poverty, poverty with a threshold anchored in time and a pan-European perspective on poverty. To do so, we work with a recently developed poverty index, the extended headcount ratio (EHC) and derive the relevant poverty lines to apply the index to poverty in Europe. We show empirically that our measure consistently captures the aspects typically monitored using a variety of indicators and yields rankings that seem more aligned with intuitions than those obtained by these individual indicators. According to our measure, Eastern Europe has a much higher level of poverty than Southern Europe, which, in turn, has a considerably higher level of poverty than North-Western Europe. In North-Western Europe, the evolution of our measure over time correlates most strongly with the at-risk-of-poverty rate, while in Southern and Eastern Europe, it correlates most strongly with at-risk-of-poverty with the threshold anchored in time

Explaining Simulations Through Self Explaining Agents

Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior. Pro-active behavior is more variable and harder to predict than reactive behavior, and therefore it might be harder to explain. However, the approach presented in this paper tries to make advantage of the agents' pro-activeness by using it to explain their behavior. The aggregation of the agents' explanations form a basis for explaining the simulation as a whole. In this paper, an agent model that is able to generate (pro-active) behavior and explanations about that behavior is introduced, and the implementation of the model is discussed. Examples show how the link between behavior generation and explanation in the model can contribute to the explanation of a simulation.Explanation, Agents, Goal-Based Behavior, Virtual Training

NKCC1 downregulation induces hyperpolarizing shift of GABA responsiveness at near term fetal stages in rat cultured dorsal root ganglion neurons

GABA A receptor-mediated neurotransmission is greatly influenced by cation-chloride cotransporter activity during developmental stages. In embryonic neurons Na–K–2Cl (NKCC1) cotransporters mediate active chloride uptake, thus increasing the intracellular chloride concentration associated with GABA-induced depolarization. At fetal stages near term, oxytocin-induced NKCC1 downregulation has been implicated in the developmental shift from depolarizing to hyperpolarizing GABA action. Mature dorsal root ganglion neurons (DRGN), however, express high NKCC1 levels and maintain high intracellular chloride levels with consequent GABA-induced depolarization.Results: Gramicidin-perforated patch-clamp recordings were used to assess the developmental change in chloride homeostasis in rat cultured small DRGN at the embryonic day 16 (E16) and 19 (E19). The results were compared to data previously obtained in fetal DRGN at E14 and in mature cells. A significant NKCC1 downregulation, leading to reduction in excitatory GABAergic transmission, was observed at E16 and E19.Conclusion: These results indicate that NKCC1 activity transiently decreases in DRGN at fetal stages near term. This developmental shift in GABAergic transmission may contribute to fetal analgesia and neuroprotection at birth

Une analyse de la privation en Belgique : comparaison entre les personnes âgées et les personnes non âgées

peer reviewe

Serious gaming for adaptive decision making of military personnel

The importance of improving adaptive decision making for the military is ever increasing, particularly in operational environments that are unfamiliar, complex, and constantly changing. This paper presents the development and testing of a serious game for training military officers in adaptive decision making. Participants were to detect rule changes in the game world, and to adjust their decisions in accordance with these changes. In an explorative study, the effectiveness of the game was tested by using in-game and outgame measures. The findings on the in-game measure suggest that the game helps participants to detect rule changes and to adapt their decision making. Despite this effect, participants' cognitive flexibility did not increase based on the findings on the out-game measures. Discussions, future directions, and training implications for the Defense organization are described