A Review of Kyoto Protocol Adoption in Russia: Joint Implementation in Focus

Russia’s role in ‘animation’ of the Kyoto Protocol was crucial. Its initial vacillation on ratification was predominantly due to political bargaining with the EU. Domestic economic rationales [i.e. impacts of emission trading and Joint Implementation (JI) projects] were important to a much lesser extent and environmental motives did not seem to play any role in the decision. Since the Protocol entered into force, there have been significant delays in complete establishment of policy implementation frameworks, which are necessary for Russia to start benefiting from JI and emission trading. Only recently, in 2007, have GHG inventories and a national registry been established and the responsibilities for implementation of the Protocol and JI among the government departments have been distributed only to a certain extent. Some constraints hindering JI projects, such as vague legislation, an unfavourable economic climate, lack of commitment to JI projects, corruption, xenophobia, state and agency ‘capture’ still remain.      

Pseudo–Modelling of Outliers for Estimation of Regression And Time Series Models

This paper documents situations where the variance inflation model for outliers has undesirable properties. The model is commonly used to accommodate outliers in a Bayesian analysis of regression and time series models. The alternative approach provided here does not suffer from these undesirable properties but gives inferences similar to those of the variance inflation model when this is appropriate. It can be used with regression, time series, and regression with correlated errors in a unified way, and adheres to the scientific principle that inference should be based on the data after obvious outliers have been discarded. Only one parameter is required for outliers; it is interpretable as the a priori willingness to remove observations from the analysis.     

Robust F-tests for linear models

The author presents a robust F-test for comparing nested linear models. It is suggested that the approach will be attractive to practitioners because it is based on the familiar F-statistic and corresponds to the common practice of reporting F-statistics after removing obvious outliers. It is calibrated in terms of a real parameter that can be directly interpreted as the willingness of the data analyst to remove observations, and the sensitivity of the F-statistic to this parameter is easily examined. The procedure is evaluated with a simulation study where a scale mixture distribution is used to generate outliers. The procedure is also applied to some data where the occurrence of an outlier is confounded with the significance of a regression term. This provides a comparison of two competing models for the data: one removing an outlier and the other including an additional regression term instead.     

Growing the Volunteer Pool: Identifying Non-Volunteers Most Likely to Volunteer

There are ongoing management and societal challenges affecting volunteering participation. These place a premium on organizations identifying individuals that currently do not volunteer but have the willingness and capacity to do so, the “Potentials”. Supplementing the limited non-volunteer literature, we seek to quantify this potential volunteer pool using constructs aligned to the willingness, capability and availability dimensions from Meijs et al.’s (Volunt Action 8:36–54, 2006) volunteerability framework. Using binary logistic regression testing with a nationally representative sample of Australian volunteers and non-volunteers, we found partial support for the framework’s willingness and capability dimensions determining volunteer status. We then applied a predictive equation to the non-volunteer sample to calculate their percentage likelihood of volunteering, to identify a cohort of “Potential” volunteers. Further testing revealed statistically significant differences between this cohort compared to other non-volunteers based on various interventions for promoting volunteering. The implications of our novel study and an associated research agenda are discussed.

     

The Statistical Analysis of Preference Data

A new statistic and a new method of analysis are proposed for data where a sample of respondents provides a preference ordering of some treatments. The new preference statistic is compared with the Friedman statistic, particularly for an example where 12 home owners each ranked four grasses. The new analysis provides a more natural and less misleading assessment of where the differences occur than an analysis based on the rank sums of the Friedman statistic. The new analysis is also more robust to deviations from the classical location problem, is not related to election methods known to have undesirable characteristics and adheres to the Condorcet criterion for election methods.     

Parents' experiences with child protection during pregnancy and post-birth

Limited research has directly sought the input of parents involved in the child protection system during pregnancy and with their infants. As the focus of these policies and practices, parents have a unique and important insight not available to others, so it is vital to obtain their input. As part of a larger Australian study, qualitative interviews were undertaken with 13 parents asking about their views and experiences. Parents predominantly became involved with child protection services during pregnancy through a prenatal report. Parents who previously had their newborn removed from their care described it as sudden and unexpected, leaving them distressed and unsupported post-removal, with a growing list of requirements for them to see their baby or for restoration to be considered. Domestic violence was a particular issue of concern for some mothers who expressed distress that their partners, perpetrators of violence, were allowed access to their infant with fewer requirements than for them. Improvements recommended by the parents included greater communication and preparation for the removal, better recognition of improvements in their situations and increased supports to be provided to parents both pre- and post-removal. Parental experiences provide an important guide to improving child protection practice with these families.     

Room for climate advocates in a coal‐focused economy? NGO influence on Australian climate policy

Many Australian environmental non‐government organisations (NGOs) have campaigned for greater political action and community awareness on human‐induced climate change for almost two decades. Australian emissions are the highest per person in the world, yet the Government's response is heavily influenced by the economically‐significant fossil fuel industry. NGO campaigners are sceptical of their campaigns' effectiveness. This paper presents three methods for evaluating the effectiveness of NGO climate change campaigns: Moyer's Movement Action Plan, Schumaker's Assessment of Political Effectiveness, and a document analysis of the influence of NGO submissions to climate policy processes. Evaluation is critical for NGO campaigns to improve their effectiveness, and evaluation criteria and methods should ideally be designed in parallel with the campaign strategy. Using these evaluation methods, it is evident that Australian NGO campaigns on climate change have been effective.     

Environmental Nonprofit Campaigns and State Competition: Influences on Climate Policy in California

Over the past 20 years, the US Federal Government has been considered to be intransigent in its response to climate change by many commentators and not-for-profit environmental advocacy organizations (nonprofits). An enduring source of pressure on the US Government has been nonprofit campaigns operating at both a state and federal level. Six US environmental nonprofits representing a diversity of resources and prominence were selected for an in-depth examination of their climate-focused campaigns. Given the resistance at the federal level, these nonprofits have undertaken state-focused campaigns to achieve adequate climate policy development. This research examined some climate campaigns in California by the selected nonprofits that have supported, enhanced, and influenced the Californian Government’s efforts to address climate change. The campaigns have gained leverage from existing state competition for economic advancement and political leadership on issues of public concern. In addition, they appear to have benefited from a high level of environmental awareness in the community, a history of progressive environmental legislation, Governor Schwarzenegger’s use of climate change to differentiate his political leadership, and strong public trust of nonprofits. Recent climate-related political pledges and legislative changes at a federal level are convergent with the nonprofit-influenced, state-level developments.     

Modified classification and regression tree splitting criteria for data with interactions

This paper proposes modified splitting criteria for classification and regression trees by modifying the definition of the deviance. The modified deviance is based on local averaging instead of global averaging and is more successful at modelling data with interactions. The paper shows that the modified criteria result in much simpler trees for pure interaction data (no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced by Clark & Pregibon's (1992) method when applied to real datasets with strong interaction effects.     

Performance of localized regression tree splitting criteria on data with discontinuities

Properties of the localized regression tree splitting criterion, described in Bremner & Taplin (2002) and referred to as the BT method, are explored in this paper and compared to those of Clark & Pregibon's (1992) criterion (the CP method). These properties indicate why the BT method can result in superior trees. This paper shows that the BT method exhibits a weak bias towards edge splits, and the CP method exhibits a strong bias towards central splits in the presence of main effects. A third criterion, called the SM method, that exhibits no bias towards a particular split position is introduced. The SM method is a modification of the BT method that uses more symmetric local means. The BT and SM methods are more likely to split at a discontinuity than the CP method because of their relatively low bias towards particular split positions. The paper shows that the BT and SM methods can be used to discover discontinuities in the data, and that they offer a way of producing a variety of different trees for examination or for tree averaging methods.