This Changes Nothing: The Paris Agreement to Ignore Reality

Abstract

At the 21st session of the Conference of the Parties to the United Nations Framework Convention on Climate Change held in Paris, France, 30 November to 11 December 2015, an Agreement was reached by the international community including 195 countries. The Agreement has been hailed, by participants and the media, as a major turning point for policy in the struggle to address human-induced climate change. The following is a short critical commentary in which I briefly explain why the Paris Agreement changes nothing. I highlight how the Agreement has been reached by removing almost all substantive issues concerning the causes of human-induced climate change and offers no firm plans of action. Instead of substantive cuts in greenhouse gas (GHG) emissions, as soon as possible, the intentions of the parties promise escalation of damages and treat worst-case scenarios as an acceptable 50:50 chance. The Paris Agreement signifies commitment to sustained industrial growth, risk management over disaster prevention, and future inventions and technology as saviour. The primary commitment of the international community is to maintain the current social and economic system. The result is denial that tackling GHG emissions is incompatible with sustained economic growth. The reality is that Nation States and international corporations are engaged in an unremitting and ongoing expansion of fossil fuel energy exploration, extraction and combustion, and the construction of related infrastructure for production and consumption. The targets and promises of the Paris Agreement bear no relationship to biophysical or social and economic reality.     

The effect of aggregation on nonlinearity

This paper investigates the interaction between aggregation and nonlinearity through a monte carlo study. Various tests for neglected nonlinearity are used to compare the power of the tests for different nonlinear models to different levels of aggregation. Three types of aggregation, namely, cross-sectional aggregation, temporal aggregation and systematic sampling are considered. Aggregation is inclined to simplify nonlinearity. The degree to which nonlinearity is reduced depends on the importance of common factor and extent of the aggregation. The effect is larger when the size of common factor is smaller and when the extent of the aggregation is larger.     

Opportunities and Risks: Models of Good Practice in Commissioning Foster-Care

Local authorities in Britain have been purchasing foster placementsand related services from independent fostering agencies orproviders (IFPs) for many years. These are often made on anunplanned or ‘spot purchased’ basis and many localauthorities have incurred significant budgetary overspends orbeen criticized for poor child-care practice. In parts of theUSA and Australia, governments have required public authoritiesto ‘outsource’ all or most of their foster-careresponsibilities to private or voluntary agencies. Where thesehave been independently evaluated, a number of deficits havebeen identified. A middle position of local authorities andIFPs entering into service level or contractual agreements hasemerged in Britain where each sector attempts to plan and matchits respective needs and services and to predict and controlcosts. This paper explores how some local authority and IFPmanagers have developed working arrangements with one anotherin order to achieve this position. At a time when the Britishgovernment is providing a strong policy steer towards inter-sectorcommissioning in foster-care, this paper suggests a frameworkfor collaboration.     

A Description and Analysis of Multi-Sectoral Fostering Practice in the United Kingdom

Correspondence to Clive Sellick, School of Social Work and Psychosocial Sciences, Elizabeth Fry Building, University of East Anglia, Norwich NR4 7TJ, UK. E-mail: c.sellick{at}uea.ac.uk Summary Foster care is the preferred placement option for children andyoung people in the public care system in Britain. In recentyears, fostering has been the subject of extensive policy andresearch review and its practice and services have been widelyexamined. Although still provided principally within the public,local authority sector, there has been a significant growthin the use of independent fostering agencies and a steady useof the fostering services of established voluntary child-careorganizations. This paper reports a recent review of innovativefostering practice in all sectors across the four countriesof the UK, which was commissioned by the Social Care Institutefor Excellence. All British fostering agencies were invitedto submit examples of what they considered to be innovativeor effective in respect of six main categories: foster carerrecruitment and training; retention and job satisfaction; placementprovision; fostering children with complex needs; service provision;and user evaluation. These were examined in the light of relevantresearch knowledge to determine the extent of ‘research-mindedness’amongst fostering agencies. The authors conclude with a critiqueof four key factors which are impacting upon contemporary fosteringpractice in Britain.     

Forecasting Performance of Information Criteria with Many Macro Series

Stock & Watson (1999) consider the relative quality of different univariate forecasting techniques. This paper extends their study on forecasting practice, comparing the forecasting performance of two popular model selection procedures, the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). This paper considers several topics: how AIC and BIC choose lags in autoregressive models on actual series, how models so selected forecast relative to an AR(4) model, the effect of using a maximum lag on model selection, and the forecasting performance of combining AR(4), AIC, and BIC models with an equal weight.     

A model for extreme wind gusts

Estimates of the largest wind gust that will occur at a given location over a specified period are required by civil engineers. Estimation is usually based on models which are derived from the limiting distributions of maxima of stationary time series and which are fitted to data on extreme gusts. In this paper we develop a model for maximum gusts which also incorporates data on hourly mean speeds through a distributional relationship between maxima and means. This joint model is closely linked to the physical processes which generate the most extreme values and thus provides a mechanism by which data on means can augment those on gusts. It is argued that this increases the credibility of extrapolation in estimates of long period return gusts. The model is shown to provide a good fit to data obtained at a location in northern England and is compared with a more traditional modelling approach, which also performs well for this site.