Occupational choice, socio-economic status and educational attainment: a study of the occupational choices and destinations of young people in the British household panel survey

The article considers young people's occupational choices at the age of 15 in relation to their educational attainment, the occupations of their parents and their actual occupations when they are in their early 20s. It uses data from the British Household Panel Survey over periods of between five and ten years. The young people in the survey are occupationally ambitious: many more aspire to professional, managerial and technical jobs than the likely availability of these occupations. In general ambitions and educational attainment and intentions are well aligned but there are also many instances of misalignment; either people wanting jobs which their educational attainments and intentions will not prepare them for, or people with less ambitious aspirations than their educational performance would justify. Children from more occupationally advantaged families are more ambitious, achieve better educationally and have better occupational outcomes than other children. However, where young people are both ambitious and educationally successful the occupational outcomes are as good for those from disadvantaged as advantaged families. In contrast, where young people are neither ambitious nor educationally successful, the outcomes for those from disadvantaged homes are very much poorer than for other young people. The article suggests that while choice is real it is also heavily constrained for many people. A possible educational implication of the study is that career interventions could be directed at under-ambitious but academically capable young people from disadvantaged backgrounds.

The transformation of earth-system observations into information of socio-economic value in GEOSS

The Group on Earth Observations System of Systems, GEOSS, is a co-ordinated initiative by many nations to address the needs for earth-system information expressed by the 2002 World Summit on Sustainable Development. We discuss the role of earth-system modelling and data assimilation in transforming earth-system observations into the predictive and status-assessment products required by GEOSS, across many areas of socio-economic interest. First we review recent gains in the predictive skill of operational global earth-system models, on time-scales of days to several seasons. We then discuss recent work to develop from the global predictions a diverse set of end-user applications which can meet GEOSS requirements for information of socio-economic benefit; examples include forecasts of coastal storm surges, floods in large river basins, seasonal crop yield forecasts and seasonal lead-time alerts for malaria epidemics. We note ongoing efforts to extend operational earth-system modelling and assimilation capabilities to atmospheric composition, in support of improved services for air-quality forecasts and for treaty assessment. We next sketch likely GEOSS observational requirements in the coming decades. In concluding, we reflect on the cost of earth observations relative to the modest cost of transforming the observations into information of socio-economic value.

Farm and socio-economic characteristics of smallholder milk producers and their influence on technology adoption in Central Mexico

In order to identify the factors influencing adoption of technologies promoted by government to small-scale dairy farmers in the highlands of central Mexico, a field survey was conducted. A total of 115 farmers were grouped through cluster analysis (CA) and divided into three wealth status categories (high, medium and low) using wealth ranking. Chi-square analysis was used to examine the association of wealth status with technology adoption. Four groups of farms were differentiated in terms of farms’ dimensions, farmers’ education, sources of incomes, wealth status, management of herd, monetary support by government and technological availability. Statistical differences (p < 0.05) were observed in the milk yield per herd per year among groups. Government organizations (GO) participated little in the promotion of the 17 technologies identified, six of which focused on crop or forage production and 11 of which were related to animal husbandry. Relatives and other farmers played an important role in knowledge diffusion and technology adoption. Although wealth status had a significant association (p < 0.05) with adoption, other factors including importance of the technology to farmers, usefulness and productive benefits of innovations together with farmers’ knowledge of them, were important. It is concluded that the analysis of the information per group and wealth status was useful to identify suitable crop or forage related and animal husbandry technologies per group and wealth status of farmers. Therefore the characterizations of farmers could provide a useful starting point for the design and delivery of more appropriate and effective extension.

The status and challenge of global fire modelling

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what essons may be learned from FireMIP.