Les agriculteurs dans la fabrique d'une nouvelle agriculture

The model of development that has governed the modernization of farming in France is increasingly coming under attack. Given this, analysing the “work” that farming performs to “translate” the criticisms with which it must cope in formulating new definitions of roles is important in order to understand changes under way in this sector. The changes undergone by farming over the past eighty years are briefly presented and then the procedures and results of a survey, conducted during the mad cow disease among beef-farmers in Burgundy, are described. Light is thus shed on the diversity of the positions that farmers have adopted with regard to the future of their occupation. An interpretation is proposed of how the distribution (and interplay between) these positions might affect agriculture. - Special issue on Agriculture and food.     

Psychological taxing in Flemish municipalities

We analyse whether the psychological pricing in the private sector has a public sector counterpart in tax policy. Analysing the main theoretical arguments for the existence of price points, and applying them to the public sector, suggests that psychological taxing reveals itself by the use of non-0 ending tax rates. The tax rate endings of the local income taxes, which are set by 308 Flemish municipalities in the fiscal year 1998, suggests the presence of psychological taxing. Non-0 endings occur more frequently in municipalities where demand for public policy is more elastic (and where, therefore, the benefits to the politicians from setting a tax just below a tax point is higher). The pre-tax income inequality and the level of the tax rate positively affect psychological taxing. The latter effect is reinforced in those municipalities where the existing tax rate is above the average tax rate in neighbouring municipalities and below their neighbours’ minimum, although this effect has a limited effect and is offset the further below the minimum the tax is set.     

A comparison of poverty in seven European countries and regions using subjective and relative measures

This paper presents comparative results on poverty in seven countries and regions of the European Community: Belgium, The Netherlands, Luxembourg, Lorraine, Ireland, Catalonia and Greece. The data are obtained from comparable socio-economic surveys in each country. Subjective as well as relative poverty lines are used. The results indicate that the subjective poverty lines are plausible in a comparative context, although the levels of the subjective standards are rather generous. The estimated equivalence scales are much flatter than the one recommended by the OECD. The extent of poverty is much greater in the peripheral EC-countries than in the central ones. Though similar factors are found to be associated with poverty in all countries, there are also important differences in the characteristics of the poor across countries. The impact of social security transfers on poverty appears to be much smaller in the southern countries Greece and Catalonia, than in the Benelux and Lorraine.     

Is there a global super-bourgeoisie?

In recent decades, accelerating processes of globalization and an increase in economic inequality in most of the world's countries have raised the question of the emergence of a new bourgeoisie integrated at the global level, sometimes described as a global super-bourgeoisie. This group would be distinguished by its unequaled level of wealth and global interconnectedness, its transnational ubiquity and concentration in the planet's major global cities, its specific culture, consumption habits, sites of sociability and shared references, and even by class consciousness and capacity to act collectively. This article successively discusses how the social sciences have examined these various dimensions of the question and begun to provide systematic empirical answers.     

Impacts of urban sprawl on species richness of plants,butterflies, gastropods and birds: not only built-up area matters

Urban growth is a major factor of global environmental change and has important impacts on biodiversity, such as changes in species composition and biotic homogenization. Most previous studies have focused on effects of urban area as a general measure of urbanization, and on few or single taxa. Here, we analyzed the impacts of the different components of urban sprawl (i.e., scattered and widespread urban growth) on species richness of a variety of taxonomic groups covering mosses, vascular plants, gastropods, butterflies, and birds at the habitat and landscape scales. Besides urban area, we considered the average age, imperviousness, and dispersion degree of urban area, along with human population density, to disentangle the effects of the different components of urban sprawl on biodiversity. The study was carried out in the Swiss Plateau that has undergone substantial urban sprawl in recent decades.Vascular plants and birds showed the strongest responses to urban sprawl, especially at the landscape scale, with non-native and ruderal plants proliferating and common generalist birds increasing at the expense of specialist birds as urban sprawl grew. Overall, urban area had the greatest contribution on such impacts, but additional effects of urban dispersion (i.e., increase of non-native plants) and human population density (i.e., increases of ruderal plants and common generalist birds) were found. Our findings support the hypothesis that negative impacts of urban sprawl on biodiversity can be reduced by compacting urban growth while still avoiding the formation of very densely populated areas.     

Bayesian adaptive dose‐escalation designs for simultaneously estimating the optimal and maximum safe dose based on safety and efficacy

The main purpose of dose‐escalation trials is to identify the dose(s) that is/are safe and efficacious for further investigations in later studies. In this paper, we introduce dose‐escalation designs that incorporate both the dose‐limiting events and dose‐limiting toxicities (DLTs) and indicative responses of efficacy into the procedure. A flexible nonparametric model is used for modelling the continuous efficacy responses while a logistic model is used for the binary DLTs. Escalation decisions are based on the combination of the probabilities of DLTs and expected efficacy through a gain function. On the basis of this setup, we then introduce 2 types of Bayesian adaptive dose‐escalation strategies. The first type of procedures, called “single objective,” aims to identify and recommend a single dose, either the maximum tolerated dose, the highest dose that is considered as safe, or the optimal dose, a safe dose that gives optimum benefit risk. The second type, called “dual objective,” aims to jointly estimate both the maximum tolerated dose and the optimal dose accurately. The recommended doses obtained under these dose‐escalation procedures provide information about the safety and efficacy profile of the novel drug to facilitate later studies. We evaluate different strategies via simulations based on an example constructed from a real trial on patients with type 2 diabetes, and the use of stopping rules is assessed. We find that the nonparametric model estimates the efficacy responses well for different underlying true shapes. The dual‐objective designs give better results in terms of identifying the 2 real target doses compared to the single‐objective designs.     

Non-parametric regression on compositional covariates using Bayesian P-splines

Methods to perform regression on compositional covariates have recently been proposed using isometric log-ratios (ilr) representation of compositional parts. This approach consists of first applying standard regression on ilr coordinates and second, transforming the estimated ilr coefficients into their contrast log-ratio counterparts. This gives easy-to-interpret parameters indicating the relative effect of each compositional part. In this work we present an extension of this framework, where compositional covariate effects are allowed to be smooth in the ilr domain. This is achieved by fitting a smooth function over the multidimensional ilr space, using Bayesian P-splines. Smoothness is achieved by assuming random walk priors on spline coefficients in a hierarchical Bayesian framework. The proposed methodology is applied to spatial data from an ecological survey on a gypsum outcrop located in the Emilia Romagna Region, Italy.