Wives and widows in medieval Flanders

Widowhood has long been regarded as the most emancipated condition that women might enjoy, affording them a freedom, agency and access to the public sphere denied their single or married counterparts. A corollary of this assumption is that most women documented as active participants in public life should be identified as widows. Based on a large corpus of references to female activity in bailiffs’ accounts and in town records and ordinances, however, this article argues that in pre-Burgundian Flanders widowhood in no way constituted a privileged status, either morally, socially, legally or economically. Flemish women were educated in order that they might achieve gainful employment; they married late and maintained control of property in marriage. Married women functioned as legal persons; they participated publicly, independently and routinely in Flemish urban life to such a degree that their subsequent activities as widows can only be understood as being in fundamental continuity with their prior behaviour as wives. This, in conjunction with the ambiguity and instability of terms for ‘women whose spouses are deceased’, destabilized the very concept of ‘widow’ itself.     

Critical objective function values in linear sum assignment problems

The linear sum assignment problem has been well studied in combinatorial optimization. Because of the integrality property, it is a linear programming problem with a variety of efficient algorithms to solve it. In the given research, we present a reformulation of the linear sum assignment problem and a Lagrangian relaxation algorithm for its reformulation. An important characteristic of the new Lagrangian relaxation method is that the optimal Lagrangian multiplier yields a critical bottleneck value. Lagrangian relaxation has only one Lagrangian multiplier, which can only take on a limited number of values, making the search for the optimal multiplier easy. The interpretation of the optimal Lagrangian parameter is that its value is equal to the price that must be paid for all objects in the problem to be assigned.     

Predicting losses of residential structures in the state of Florida by the public hurricane loss evaluation model

As an environmental phenomenon, hurricanes cause significant property damage and loss of life in coastal areas almost every year. Although a number of commercial loss projection models have been developed to predict the property losses, only a handful of studies are available in the public domain to predict damage for hurricane prone areas. The state of Florida has developed an open, public model for the purpose of probabilistic assessment of risk to insured residential property associated with wind damage from hurricanes. The model comprises three components; viz. the atmospheric science component, the engineering component and the actuarial science component. The atmospheric component includes modeling the track and intensity life cycle of each simulated hurricane within the Florida threat area. Based on historical hurricane statistics, thousands of storms are simulated allowing determination of the wind risk for all residential Zip Code locations in Florida. The wind risk information is then provided to the engineering and actuarial components to model damage and average annual loss, respectively. The actuarial team finds the county-wise loss and the total loss for the entire state of Florida. The computer team then compiles all information from atmospheric science, engineering and actuarial components, processes all hurricane related data and completes the project. The model was submitted to the Florida Commission on Hurricane Loss Projection Methodology for approval and went through a rigorous review and was revised as per the suggestions of the commission. The final model was approved for use by the insurance companies in Florida by the commission. At every stage of the process, statistical procedures were used to model various parameters and validate the model. This paper presents a brief summary of the main components of the model (meteorology, vulnerability and actuarial) and then focuses on the statistical validation of the same.     

Authors’ responses to the discussion on “Predicting losses of residential structures in the state of Florida by the Public Hurricane Loss Evaluation Model”

Hurricanes threaten the Florida coast line every year and are capable of causing catastrophic losses. The Public Hurricane Loss Model was developed in response to the need for having an open transparent model to predict the above losses. The results were summarized in the paper “Predicting Losses of Residential Structures in the State of Florida by the Public Hurricane Loss Model” which was subsequently a subject of discussion by experts in Meteorology, Engineering, Actuarial Sciences and Statistics. The present paper presents a response to the discussions on the above mentioned article.     

New frontiers in demography and social psychology

The topics of demography are those of human fate: birth, illness, marriage, occupation, and death. The methods of demography therefore relate global rates to major events, submerging the individual decision. The social psychologist observes the regularities of people's behavior in different social conditions and builds models from individual decisions. Since he looks at patterns independent of the event, the kind of event does not matter, and he tends to concentrate on trivial events which are amenable to research.To the degree that man has obtained control over his environment, he is able to look at demographic events as less than fate. Social conditions have also given more control to the individual over many events over which he had no control previously, such as choice of a marriage partner or an occupational career. Thus, the classical methods of demography are frequently insufficient to deal with demographic data, and abrupt changes may occur because of vagaries of individual decisions. The more the demographic trends can be affected by individual decisions, the more the methods of social psychology become useful in understanding changes in population composition.The possibilities of micro-demography, of building up demographic trends from individual decisions, become stronger as more individual control can be exerted over the events. Such disparate events as control of infectious disease, air pollution, birth control, civil rights, and changes in the educational system and occupational structure have given individuals more control over different demographic variables, made the study of individual decisions with demographic consequences important, and led to joint efforts by demographers and social psychologists.     

Program decisions : Evaluating a bird in the hand versus two in the bush

In new programs that have not reached full effectiveness, or in programs that are designed to produce future benefits (i.e., become “institutionalized”), evaluations that fail properly to assess future performance may bias decisions against the programs. For such programs, consideration of future benefits may significantly enhance the assessment of their cost-effectiveness. This paper describes an evaluation methodology based on decision theory that can take future benefits into account in evaluating a program. The methodology was applied to the Metropolitan Atlanta Crime Commission (MACC) Community Anti-Crime Project and indicated the potential for substantial future benefits subsequent to cessation of federal funding. The implications of use of this methodology and the MACC results for the overall Community Anti-Crime Program are also discussed.     

Studying Heuristic-Systematic Processing of Risk Communication

Using a model of risk information seeking and processing developed by Griffin, Dunwoody, and Neuwirth (1999), this study looks at predictors of the processing strategies that people apply to health risk information. Specifically, this article focuses on one relationship within the model--the relationship between perceived amount of information needed to deal with a risk and heuristic-systematic processing. Perceived amount of information needed refers to the gap between one's understanding of a risk and the level of understanding that one needs in order to make a decision about that risk. Building on the work of Chaiken (cf. 1980), the Griffin et al. model predicts--and finds--that the larger the gap, the more likely one will process information systematically. The study employs a novel measure of information processing in a survey setting by sending actual information to participants and then asking them how they attended to it; the researchers evaluate this strategy. Finally, the researchers discuss how these findings might help agencies and practitioners create more effective risk messages.