How are policies implemented in children's services? Developing an initial programme theory to evaluate the implementation of the new Child Sexual Exploitation guidance in Wales

Although children's social care is an area rich in guidance, there is very little research looking at the implementation of new policies in the United Kingdom. In this article, we report on the first stage of a realist evaluation of the implementation of the new Safeguarding Children from Child Sexual Exploitation guidance in Wales. We discuss the development of an initial programme theory, for which we conducted semi-structured interviews with practitioners and managers in three local authorities. We developed programme theories across three areas: policy nature and development, implementation plans and organizational context. Findings suggest that, for policies to produce a significant impact on practice, they need to be sufficiently different to social workers' current perceptions of practice. Second, we found that the coordination between national and local policies is critical for successful implementation as contradictions between them might lead to confusion in what local teams should prioritize. Finally, our findings highlight the importance of effective communication of policy changes, as well as a supportive organizational culture to strengthen implementation in local contexts. These findings illustrate the complexity of policy implementation and the need for policymakers to consider the meaningful involvement of local practitioners in national policy development.     

Participation as a right to the city: Iranian children’s perspectives about their inclusion in urban decision-making

To assess children's willingness to participate in decision-making about urban environments, Iranian children were invited to tell their stories about child inclusion in city affairs. The findings demonstrate children's enthusiasm to have a say, their suggestions of how their ideas can be integrated into planning, and their competency for participation. Despite their willingness, participants indicated awareness of patriarchal cultural views of children and childhood which continue to exclude them from planning involvement. Being denied the exercise of their rights to the city generates a marginalised status, alienating children from achieving appropriate engagement.     

Spatial Disaggregation of Social Indicators: An Info-Metrics Approach

In this paper we propose a methodology to obtain social indicators at a detailed spatial scale by combining the information contained in census and sample surveys. Similarly to previous proposals, the method proposed here estimates a model at the sample level to later project it to the census scale. The main novelties of the technique presented are that (i) the small-scale mapping produced is perfectly consistent with the aggregates -regional or national- observed in the sample, and (ii) it does not require imposing strong distributional assumptions. The methodology suggested here follows the basics presented on Golan (2018) by adapting a cross-moment constrained Generalized Maximum Entropy (GME) estimator to the spatial disaggregation problem. This procedure is compared with the equivalent methodology of Tarozzi and Deaton (2009) by means of numerical experiments, providing a comparatively better performance. Additionally, the practical implementation of the methodology proposed is illustrated by estimating poverty rates for small areas for the region of Andalusia (Spain).

     

Crown width models for woody plant species growing in urban areas of the U.S.

Urban Ecosystems - Crown widths of woody plant species growing in urban areas are of considerable importance as an overall indicator of health and also serve as an important factor for assessing...     

Nonparametric methods in factorial designs

Summary In this paper, we summarize some recent developments in the analysis of nonparametric models where the classical models of ANOVA are generalized in such a way that not only the assumption of normality is relaxed but also the structure of the designs is introduced in a broader framework and also the concept of treatment effects is redefined. The continuity of the distribution functions is not assumed so that not only data from continuous distributions but also data with ties are included in this general setup. In designs with independent observations as well as in repeated measures designs, the hypotheses are formulated by means of the distribution functions. The main results are given in a unified form. Some applications to special designs are considered, where in simple designs, some well known statistics (such as the Kruskal-Wallis statistic and the χ²-statistic for dichotomous data) come out as special cases. The general framework presented here enables the nonparametric analysis of data with continuous distribution functions as well as arbitrary discrete data such as count data, ordered categorical and dichotomous data. Received: October 13, 1999; revised version: June 26, 2000     

Bayesian forecasting for AR(1) models with normal coefficients

This paper presents a Bayesian solution to the problem of time series forecasting, for the case in which the generating process is an autoregressive of order one, with a normal random coefficient. The proposed procedure is based on the predictive density of the future observation. Conjugate priors are used for some parameters, while improper vague priors are used for others.     

Quantifying the Effects of Expert Selection and Elicitation Design on Experts’ Confidence in Their Judgments About Future Energy Technologies

Expert elicitations are now frequently used to characterize uncertain future technology outcomes. However, their usefulness is limited, in part because: estimates across studies are not easily comparable; choices in survey design and expert selection may bias results; and overconfidence is a persistent problem. We provide quantitative evidence of how these choices affect experts’ estimates. We standardize data from 16 elicitations, involving 169 experts, on the 2030 costs of five energy technologies: nuclear, biofuels, bioelectricity, solar, and carbon capture. We estimate determinants of experts’ confidence using survey design, expert characteristics, and public R&D investment levels on which the elicited values are conditional. Our central finding is that when experts respond to elicitations in person (vs. online or mail) they ascribe lower confidence (larger uncertainty) to their estimates, but more optimistic assessments of best‐case (10th percentile) outcomes. The effects of expert affiliation and country of residence vary by technology, but in general: academics and public‐sector experts express lower confidence than private‐sector experts; and E.U. experts are more confident than U.S. experts. Finally, extending previous technology‐specific work, higher R&D spending increases experts’ uncertainty rather than resolves it. We discuss ways in which these findings should be seriously considered in interpreting the results of existing elicitations and in designing new ones.     

International Financial Integration and Its Distinctions in Transition Economies

We discuss the main tendencies and forms of international financial integration in both developing and developed economies. Integration of financial markets is a topic of economic debates especially for developed and transition economies, particularly Armenia, because it is the most effective way of overcoming the main problems of financial-sector development of transition economies. But there are many problems on the way of financial integration, which are summarized into four groups: institutional problems, legislative problems, macroeconomic instability, and technical problems. All of these problems are analyzed in the article for Armenia, though they are quite relevant for most transition countries.