The New Deal: jeopardised by the geography of unemployment?

The New Deal is the Labour government's flagship programme to "end the tragic waste of youth and long-term unemployment" by getting people off welfare benefits and into work. This paper argues that the principal weakness of the New Deal is that it seeks to influence the character of labour supply (i.e. the motivation and skills of the unemployed) while neglecting the state of labour demand, which varies greatly between places. The uneven geography of unemployment in the UK is likely to have a crucial bearing on the programme's impact and effectiveness, but this has been largely ignored in its development. The paper outlines some of the practical consequences of this imbalance and suggests how it could be rectified for the programme to be more effective

Employment of ex-prisoners with mental health problems, a realistic evaluation protocol

Background Offenders with a mental illness are routinely excluded from vocational services due to their mental health. Employment has shown to be very important in improving mental health, reducing recidivism, and connecting people to society. This study examines the effectiveness of an established intervention which is relatively untested in this population, Individual Placement and Support (IPS), to help offenders with mental health problems into competitive employment. The overall research question is whether IPS is effective in gaining and sustaining competitive employment for offenders with a Severe Mental Illness (SMI). The context is an English criminal justice setting across different populations. The study will also measure non-vocational outcomes such as recidivism, mental health and social stability. Methods/Design A Realistic Evaluation (RE) design will address the questions “What works, for whom, and in what circumstances?” This study includes pre and post comparisons for a cohort of approximately 20 people taking part in IPS, and a similar number of controls, over a one year period. The RE also consists of interviews with practitioners and offenders in order to understand how IPS works and develops within the criminal justice system (CJS). By applying this framework the research can go from discovering whether IPS works, to how and why (or why not) IPS works. This is achieved by examining where the intervention is occurring (Context (C)), the mechanisms (M) that create particular behaviours, and how the outcomes (O) from the intervention all come together (CMOs). Employment outcomes will also be examined for all participants. Discussion By applying RE the research will permit inferences to be drawn about how and why (or why not) IPS works, by examining context, mechanisms and outcomes. IPS has never been implemented within the CJS in the United Kingdom. As a result, this evaluative research will not only provide a novel insight into the core research areas, but also how the intervention can be improved for others in the future

The Dark Side of Transfer Pricing: Its Role in Tax Avoidance and Wealth Retentiveness

In conventional accounting literature, ?transfer pricing? is portrayed as a technique for optimal allocation of costs and revenues amongst divisions, subsidiaries and joint ventures within a group of related entities. Such representations of transfer pricing simultaneously acknowledge and occlude how it is deeply implicated in processes of wealth retentiveness that enable companies to avoid taxes and facilitate the flight of capital. A purely technical conception of transfer pricing calculations abstracts them from the politico-economic contexts of their development and use. The context is the modern corporation in an era of globalized trade and its relationship to state tax authorities, shareholders and other possible stakeholders. Transfer pricing practices are responsive to opportunities for determining values in ways that are consequential for enhancing private gains, and thereby contributing to relative social impoverishment, by avoiding the payment of public taxes. Evidence is provided by examining some of the transfer prices practices used by corporations to avoid taxes in developing and developed economies

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling

Approaches to advance scientific understanding of macrosystems ecology

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological pat- terns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require valida- tion, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Anthromes dispaying evidence of weekly cycles in active fire data cover 70% of the global land surface

Across the globe, human activities have been gaining importance relatively to climate and ecology as the main controls on fire regimes and consequently human activity became an important driver of the frequency, extent and intensity of vegetation burning worldwide. Our objective in the present study is to look for weekly cycles in vegetation fire activity at global scale as evidence of human agency, relying on the original MODIS active fire detections at 1 km spatial resolution (MCD14ML) and using novel statistical methodologies to detect significant periodicities in time series data. We tested the hypotheses that global fire activity displays weekly cycles and that the weekday with the fewest fires is Sunday. We also assessed the effect of land use and land cover on weekly fire cycle significance by testing those hypotheses separately for the Villages, Settlements, Croplands, Rangelands, Seminatural, and Wildlands anthromes. Based on a preliminary data analysis of the daily global active fire counts periodogram, we developed an harmonic regression model for the mean function of daily fire activity and assumed a linear model for the de-seasonalized time series. For inference purposes, we used a Bayesian methodology and constructed a simultaneous 95% credible band for the mean function. The hypothesis of a Sunday weekly minimum was directly investigated by computing the probabilities that the mean functions of every weekday (Monday to Saturday) are inside the credible band corresponding to mean Sunday fire activity. Since these probabilities are small, there is statistical evidence of significantly fewer fires on Sunday than on the other days of the week. Cropland, rangeland, and seminatural anthromes, which cover 70% of the global land area and account for 94% of the active fires analysed, display weekly cycles in fire activity. Due to lower land management intensity and less strict control over fire size and duration, weekly cycles in Rangelands and Seminatural anthromes, which jointly account for 53.46% of all fires, although statistically significant are weaker than those detected in Croplandsinfo:eu-repo/semantics/publishedVersio

Probabilistic fire spread forecast as a management tool in an operational setting

Background: An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events. Results: Uncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected. Conclusion: This information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these firesinfo:eu-repo/semantics/publishedVersio

Physicians are a key to encouraging cessation of smoking among people living with HIV/AIDS: a cross-sectional study in the Kathmandu Valley, Nepal

BackgroundHIV care providers may be optimally positioned to promote smoking behaviour change in their patients, among whom smoking is both highly prevalent and uniquely harmful. Yet research on this front is scant, particularly in the developing country context. Hence, this study describes smoking behaviour among people living with HIV/AIDS (PLWHA) in the Kathmandu Valley of Nepal, and assesses the association between experience of physician-delivered smoking status assessment and readiness to quit among HIV-positive smokers.MethodsWe conducted a cross-sectional survey of PLWHA residing in the Kathmandu Valley, Nepal. Data from 321 adult PLWHA were analyzed using multiple logistic regression for correlates of current smoking and, among current smokers, of motivational readiness to quit based on the transtheoretical model (TTM) of behaviour change.ResultsOverall, 47% of participants were current smokers, with significantly higher rates among men (72%), ever- injecting drug users (IDUs), recent (30-day) alcohol consumers, those without any formal education, and those with higher HIV symptom burdens. Of 151 current smokers, 34% were thinking seriously of quitting within the next 6 months (contemplation or preparation stage of behaviour change). Adjusting for potential confounders, experience of physician-delivered smoking status assessment during any visit to a hospital or clinic in the past 12 months was associated with greater readiness to quit smoking (AOR = 3.34; 95% CI = 1.05,10.61).ConclusionsRoughly one-third of HIV-positive smokers residing in the Kathmandu Valley, Nepal, are at the contemplation or preparation stage of smoking behaviour change, with rates significantly higher among those whose physicians have asked about their smoking status during any clinical interaction over the past year. Systematic screening for smoking by physicians during routine HIV care may help to reduce the heavy burden of smoking and smoking-related morbidity and mortality within HIV-positive populations in Nepal and similar settings

Africa and the global carbon cycle

The African continent has a large and growing role in the global carbon cycle, with potentially important climate change implications. However, the sparse observation network in and around the African continent means that Africa is one of the weakest links in our understanding of the global carbon cycle. Here, we combine data from regional and global inventories as well as forward and inverse model analyses to appraise what is known about Africa's continental-scale carbon dynamics. With low fossil emissions and productivity that largely compensates respiration, land conversion is Africa's primary net carbon release, much of it through burning of forests. Savanna fire emissions, though large, represent a short-term source that is offset by ensuing regrowth. While current data suggest a near zero decadal-scale carbon balance, interannual climate fluctuations (especially drought) induce sizeable variability in net ecosystem productivity and savanna fire emissions such that Africa is a major source of interannual variability in global atmospheric CO(2). Considering the continent's sizeable carbon stocks, their seemingly high vulnerability to anticipated climate and land use change, as well as growing populations and industrialization, Africa's carbon emissions and their interannual variability are likely to undergo substantial increases through the 21st century