Superstar cities with high-paying creative-class jobs, venture capital, and innovation are thought to be more unequal. We analyze mixing in neighbourhoods by income, education and occupation, relating this intra-urban measure with regional productivity indicators. Using non-overlapping census units and a machine-learning estimation technique that iterates over all combinations of economic, business, housing and cultural indicators, we identify ‘ingredients’ associated with economically and socially diverse neighbourhoods. Broad support is not found that neighbourhoods in superstar regions are less mixed; however, overrepresentation in creative occupations stymies mixing as does a combination of weak economic fundamentals with high shares of new housing.

This study explores whether the broader context in which a city is located impacts the change in crime levels over the subsequent decade. This study uses a wide range of cities (those with a population of at least 10,000), over a long period of time (from 1970 to 2010). We test and find that although cities with larger population and those surrounded by a county with a larger population typically experience larger increases in crime over the subsequent decade, cities experiencing an increase in population during the current decade experience crime decreases. The study finds that cities with higher average income experience greater subsequent crime decreases, and those surrounded by counties with larger unemployment increases experience crime increases. Higher levels of income inequality and racial/ethnic heterogeneity are associated with increasing crime rates, and increasing inequality and racial/ethnic heterogeneity in the surrounding county are associated with further increases. Furthermore, this relationship has strengthened since 1970, suggesting that both scales of inequality are even more important from a public safety perspective. Finally, we tested the time invariance of these relationships, and showed that the magnitude of the relationship between city-level inequality and increasing crime has increased over the study period.

This study introduces filtering theory from housing economics to criminology and measures the age of housing as a proxy for deterioration and physical disorder. Using data for Los Angeles County in 2009 to 2011, negative binomial regression models are estimated and find that street segments with older housing have higher levels of all six crime types tested. Street segments with more housing age diversity have higher levels of all crime types, whereas housing age diversity in the surrounding ½-mile area is associated with lower levels of crime. Street segments with detached single-family units generally had less crime compared with other types of housing. Street segments with large apartment complexes (five or more units) generally have more crime than those with small apartment complexes and duplexes.

This paper is an empirical analysis of employment centres in the Los Angeles region from 1997 to 2014. Most extant work on employment centres focuses on identification methodology or their dynamics during a period of industrial restructuring from 1980 to 2000. We analyse employment centres using point-based, rather than census tract-based employment data and a non-parametric identification method with a single concept of proximity. We focus on changes across five key industries: knowledge-intensive business services (KIBS), retail, creative, industrial and high-tech, emphasising changes in centre composition as well as their boundaries. Results show far greater change across centres than previous longitudinal studies. Only 43% of the land area that is in an employment centre is part of one in both 1997 and 2014. Using a persistence score, centres range from stable to highly fluctuating, but emerging, persisting and dying centres are found in core and fringe areas alike. KIBS are most associated with stable centres, while high tech employment is attracted toward emerging areas and retail exists throughout. Emerging centres are more likely to have greater accessibility, while industrial employment becomes far more concentrated in centres by 2014.

This article analyzes the impact of changing housing and neighborhood characteristics on the accessibility of neighborhood businesses using Long Beach, California, as a case study. Although advocates of smart growth and New Urbanism encourage land use mixing, aggregate-level analysis can be too coarse to pick up on fine-grained aspects of urban streetscapes. This study uses assessor parcel records and a point-based business establishment data set to analyze city-wide patterns of accessibility from individual dwelling units to thirty-one types of neighborhood businesses, including grocery stores, service shops, drug stores, doctor's offices, and banks. Regression results compare parcel-level and neighborhood-level drivers of accessibility between 2006 and 2015 to gauge the aggregated effect of recent economic, demographic, and built environment changes on this aspect of urban spatial structure. Larger homes in older, multiunit buildings and higher income neighborhoods show substantial increases in accessibility to most establishment types, suggesting a trend toward both greater accessibility and larger dwelling units—despite the traditional trade-off between access and space. Although gradual increases in home and business density increased overall accessibility over this period, weaker neighborhood-level results indicate that this trend is less pronounced in high-poverty and non-white areas.

Much of the work concerning economic dynamism has focused on its aggregate-level implications, while there have been rising concerns about business displacement at the community or neighborhood level. In this article, we analyze this important (restructuring) process using detailed establishment-level business information and explore how it manifests itself across space within the Los Angeles—Long Beach—Santa Ana, CA Urbanized Area. We also investigate the association between business churning and neighborhood-level housing vacancy rates to understand the implications of dramatic changes in the business landscape. We find that housing vacancies are more likely to increase in urban neighborhoods with a higher establishment death rate, while the creation of new businesses can mitigate the association to some extent. We also detect substantial variation across decades not only in the spatial distribution of business churning but also in its association with housing vacancy rates, suggesting the evolving nature of business dynamics and their implications.

Scholars of New Urbanism have suggested that mixing along various dimensions in neighborhoods (e.g., income, race/ethnicity, land use) may have positive consequences for neighborhoods, particularly for economic dynamism. A challenge for empirically assessing this hypothesis is that the impact of mixing may depend on various socio-demographic characteristics of the neighborhood and takes place in a complex fashion that cannot be appropriately handled by traditional statistical analytical approaches. We utilize a rarely used, innovative estimation technique—kernel regularized least squares—that allows for nonparametric estimation of the relationship between various neighborhood characteristics in 2000 and the change in average household income in the neighborhood from 2000 to 2010. The results demonstrate that the relationships between average income growth and both income mixing and racial/ethnic mixing are contingent upon several neighborhood socio-demographic “ingredients”. For example, racial mixing is positively associated with average income over time when it occurs in neighborhoods with a high percentage of Latinos or immigrants, high population density, or high housing age mixing. Income mixing is associated with worsening average household income in neighborhoods with more poverty, unemployment, immigrants, or population density. It appears that considering the broader characteristics of the neighborhood is important for understanding economic dynamism.

Rationale and objectives

Ultrasound is used increasingly in medical practice as a tool for focused bedside diagnosis and technical assistance during procedures. Widespread availability of small portable units has put this technology into the hands of many physicians and medical students who lack dedicated training, leaving the education and introduction of this key modality increasingly to physicians from other specialties. We developed a radiology-led program to teach ultrasound skills to preclinical medical students.

Materials and methods

To develop this new ultrasound program we 1) established a program leader, 2) developed teaching materials, 3) created a hands-on interactive program, and 4) recruited the necessary instructors. The program was piloted with the first-year medical student class of 154 students. The introductory session was assessed by pre- and post-activity Likert scale-based surveys.

Results

Of 154 (68.8%) students, 106 completed a voluntary online survey before starting the program and 145 students (94.2%) completed a voluntary survey after the session. Students found the program educationally valuable (4.64 of 5) and reported that it improved their understanding of ultrasound imaging (4.7 of 5). Students' reported confidence in identifying abdominal organs, intra-abdominal fluid, and Morison pouch that was significantly higher on the postactivity survey compared to the presurvey (P < .001 for all).

Conclusions

We piloted a radiology-led program to teach ultrasound skills to preclinical medical students. Students found the experience enjoyable and educationally valuable.