Eyes on the Block: Measuring Urban Physical Disorder Through In-Person Observation

In this paper, we present results from measuring physical disorder in Los Angeles neighborhoods. Disorder measures came from structured observations conducted by trained field interviewers. We examine inter-rater reliability of disorder measures in depth. We assess the effects of observation conditions on the reliability of reporting. Finally, we examine the relationships between disorder, other indicators of neighborhood status, and selected individual outcomes.Our results indicate that there is considerable variation in the level of agreement among independent observations across items, although overall agreement is moderate to high. Durable indicators of disorder provide the most reliable measures of neighborhood conditions. Circumstances of observation have statistically significant effects on the observers’ perceived level of disorder. Physical disorder is significantly related to other indicators of neighborhood status, and to children’s reading and behavior development.This result suggests a need for further research into the effects of neighborhood disorder on children.     

Exploratory data structure comparisons: three new visual tools based on principal component analysis

Datasets are sometimes divided into distinct subsets, e.g. due to multi-center sampling, or to variations in instruments, questionnaire item ordering or mode of administration, and the data analyst then needs to assess whether a joint analysis is meaningful. The Principal Component Analysis-based Data Structure Comparisons (PCADSC) tools are three new non-parametric, visual diagnostic tools for investigating differences in structure for two subsets of a dataset through covariance matrix comparisons by use of principal component analysis. The PCADCS tools are demonstrated in a data example using European Social Survey data on psychological well-being in three countries, Denmark, Sweden, and Bulgaria. The data structures are found to be different in Denmark and Bulgaria, and thus a comparison of for example mean psychological well-being scores is not meaningful. However, when comparing Denmark and Sweden, very similar data structures, and thus comparable concepts of well-being, are found. Therefore, inter-country comparisons are warranted for these countries.     

Grandparents raising grandchildren: negotiating the complexities of role‐identity conflict

The purpose of this qualitative study was to better understand the experience of grandparents who are raising their grandchildren in New South Wales, Australia. In‐depth interviews were conducted with 34 grandparents and their narratives transcribed and studied using paradigmatic analysis to reveal common themes among the stories told. Identity theory further informed the discussion of these findings. Woven throughout the grandparent narratives is a story of paradox – of experience simultaneously made up of pain/pleasure, myth/reality, inclusion/exclusion, being deserving/undeserving, visible/invisible and voiced/silenced. The findings signal a significant role‐identity conflict for grandparents who are parenting grandchildren. This study points to the need for policy and practice that more closely reflects the complexity of experience associated with the grandparent‐as‐parent role.     

Non‐Parametric Estimation of the Conditional Distribution of the Interjumping Times for Piecewise‐Deterministic Markov Processes

This paper presents a non‐parametric method for estimating the conditional density associated to the jump rate of a piecewise‐deterministic Markov process. In our framework, the estimation needs only one observation of the process within a long time interval. Our method relies on a generalization of Aalen's multiplicative intensity model. We prove the uniform consistency of our estimator, under some reasonable assumptions related to the primitive characteristics of the process. A simulation study illustrates the behaviour of our estimator.     

Nowcasting GDP in Real Time: A Density Combination Approach

In this article, we use U.S. real-time data to produce combined density nowcasts of quarterly Gross Domestic Product (GDP) growth, using a system of three commonly used model classes. We update the density nowcast for every new data release throughout the quarter, and highlight the importance of new information for nowcasting. Our results show that the logarithmic score of the predictive densities for U.S. GDP growth increase almost monotonically, as new information arrives during the quarter. While the ranking of the model classes changes during the quarter, the combined density nowcasts always perform well relative to the model classes in terms of both logarithmic scores and calibration tests. The density combination approach is superior to a simple model selection strategy and also performs better in terms of point forecast evaluation than standard point forecast combinations.     

Public meetings as sources of citizen input: Comparing attendees with citizens at large

Although public meetings are the most frequently used method for obtaining citizen input into public decision-making, there is little systematic evidence comparing attendees with citizens at large. This paper addresses this gap in the literature by analyzing results from a series of public meetings and a random-sample telephone survey. The public meetings and telephone survey were conducted in Hillsborough County, Florida to obtain citizen input for the purpose of establishing spending priorities for more than $39 million in federal block grant funds. Findings include representation at public meetings on a number of factors, including race, Hispanic ethnicity, and low-income status. Attendees favor redistributive activities more often than citizens at large; however, both attendees and the general public agree on the importance of funding activities serving certain vulnerable populations, including seniors, persons with disabilities, and victims of domestic violence.     

Location of Public Goods and the Calculus of Voting: The Seattle Monorail Referendum*

Objectives. In this article we explore how the geographic location of a proposed public good on the ballot in a local referendum influences voting turnout. We argue that voters who live farther away from the good, and are thus likely to bear the cost of the good but have no access to it, would be more motivated to turn out in the election. Drawing on the cost‐orientation hypothesis, or negativity effect, “that people are more strongly motivated to avoid losses than to approach gains,” we expect these voters to derive higher expressive benefits from the act of voting relative to those of voters located closer to the good. Methods. We examine voting turnout in the 2002 referendum in the City of Seattle on the proposed construction of a monorail. We conduct our study at the precinct level using spatial tools of analysis. We evaluate the effect of accessibility on turnout by means of a curvilinear model that incorporates demographic and political variables. Results. We find that voting turnout is determined partly by accessibility. Turnout is higher in precincts located farther away from the monorail line than in precincts located relatively closer to the line. Partisanship conditions this effect. Conclusions. This study provides tentative support for linking voter turnout to the negativity effect via expressive benefits. Voters' location in relation to a public good may affect directly their political behavior by means of their perceived net gains or losses from the good.