Interregional migration 'wage premia': the case of creative and science and technology graduates in the UK

We analyze the migration behavior of graduates from UK universities with a focus on the salary benefits they receive from the migration process. We focus on sequential interregional migration and specifically examine the case of Science, Technology, Engineering and Mathematics (STEM) and Creative subject graduates. Our analysis differs from previous studies in that it accounts explicitly for migrant selectivity through propensity score matching, and it also classifies graduates into different migration behavior categories. Graduates were classified according to their sequential migration behavior first from their pre-university domicile to university and then from university to first job post-graduation. Our results show that ‘repeat migration’, as expected, is associated with the highest wage premium (around 15%). Other migration behaviors are also advantageous although this varies across different types of graduates. Creative graduates, for instance, do not benefit much from migration behaviors other than repeat migration. STEM graduates, on the contrary, benefit from both late migration and staying in the university area to work.

How robust are observed and simulated precipitation responses to tropical ocean warming?

Robust responses and links between the tropical energy and water cycles are investigated using multiple datasets and climate models over the period 1979-2006. Atmospheric moisture and net radiative cooling provide powerful constraints upon future changes in precipitation. While moisture amount is robustly linked with surface temperature, the response of atmospheric net radiative cooling, derived from satellite data, is less coherent. Precipitation trends and relationships with surface temperature are highly sensitive to the data product and the time-period considered. Data from the Special Sensor Microwave Imager (SSM/I) produces the strongest trends in precipitation and response to warming of all the datasets considered. The tendency for moist regions to become wetter while dry regions become drier in response to warming is captured by both observations and models. Citation: John, V. O., R. P. Allan, and B. J. Soden (2009), How robust are observed and simulated precipitation responses to tropical ocean warming?

Models, mathematics and meaning in interdisciplinary research

Interdisciplinary research presents particular challenges for unambiguous communication. Frequently, the meanings of words differ markedly between disciplines, leading to apparent consensus masking fundamental misunderstandings. Researchers can agree on the need for models, but conceive of models fundamentally differently. While mathematics is frequently seen as an elitist language reinforcing disciplinary distinctions, both mathematics and modelling can also offer scope to bridge disciplinary epistemological divisions and create common ground on which very different disciplines can meet. This paper reflects on the role and scope for mathematics and modelling to present a common epistemological space in interdisciplinary research spanning the social, natural and engineering sciences.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Departmental differences in attitudes to special educational needs in the secondary school

As trends in favour of inclusion continue, questions arise concerning the extent to which teachers in mainstream schools feel prepared for the task of meeting pupils' special educational needs. Little previous research has considered how the subject taught impacts upon the attitudes of mainstream teachers towards pupils with special educational needs. In this article, Jean Ellins, research fellow at the University of Birmingham, and Jill Porter, senior lecturer at the University of Bath, report on their research into the attitudes of teachers in one mainstream secondary school. Building a detailed case study using documents, records of pupil progress, an interview and a questionnaire using a Likert-type attitude scale and open-ended questions, these researchers set out to explore distinctions between the attitudes of teachers working in different departments. Their findings suggest that the teachers of the core subjects, English, mathematics and science, had less positive attitudes than their colleagues. Further, pupils with special educational needs made least progress in science where teacher attitudes were the least positive. Jean Ellins and Jill Porter review the implications of these findings and make recommendations for future practice and further enquiry.