The gentrification of “Boerum Hill”: Neighborhood change and conflicts over definitions

The article presents a case history of a gentrifying neighborhood, with special reference to the interplay between cultural artifacts and the forces of the political economy. In Boerum Hill, a neighborhood in Brooklyn, newly arriving middle-class homeowners used various political and cultural methods, including changes in nomen-clature, house tours, manipulation of boundaries and an attempt to secure historic landmark status, in order to enforce their definition of what the neighborhood should be. A countermovement then emerged on the part of older residents, who, using a different set of cultural referents (based on the notion of ethnic pride), sought to enforce a different definition. The author proposes that while the neighborhood is a socially constructed entity, the resources with which this construction takes place are unequally distributed. Moreover, as the notion of neighborhood has become increasingly politically salient in recent years, the author suggests that cultural conflicts over the definition of neighborhoods have become a feature of urban politics.     

Understanding manager resistance to blockchain systems

Blockchain technology has received much attention in the media and there is an increasing interest amongst organizations within financial services due to the potential benefits. As blockchain-based systems are a nascent technology, the requirements of the technology need to be understood, to allow blockchain systems to be successfully integrated within financial service organizations. There are gaps in academic research in understanding how managers evaluate the value of a blockchain-based system. This study develops a model to explain manager resistance to implementing blockchain-based systems in financial services organizations. This research advances the theoretical understanding of managers’ perspectives on blockchain-based systems and models their resistance to blockchain technology.     

The missing bridge: How immigrant networks keep Americans out of dirty jobs

Immigrants are over half of the new entrants in occupations in southwestern labor markets that range from farmworker to janitor to engineering professor. This paper explains how the availability of immigrant workers changes employment practices in ways that push and pull Americans out of jobs which remain "dirty" or unattractive to U.S. workers. An immigrant network that eventually takes over an enterprise's jobs can begin by accident or design. Accidental immigrant takeovers begin with pioneer workers who persist in high turnover jobs such as seasonal farmworker. These workers offer to bring their friends and relatives to fill vacancies as they occur. Takeovers by design sometimes follow a strike in which immigrants are recruited to be strikebreakers. After immigrants dominate the workforce, the language and culture of the workplace change in ways that make American workers feel out-of-place. Employers feel under no compulsion to upgrade dirty jobs as long as immigrant workers are available, so the technology and productivity of immigrant-enclave jobs tend to be frozen, guaranteeing that dirty jobs get less and less attractive to Americans. Indeed, industries dependent on immigrant workers often turn protectionist when they realize that even low immigrant wages are not sufficient to ensure their survival in the global marketplace. In this way, Americans lose out in several ways: They must compete directly with immigrant workers in the labor market, and then pay higher prices for the goods produced by immigrant workers because the industries preserved by them demand protection from imports. This paper will explore the manner in which immigrant networks displace Americans from dirty jobs and how the availability of immigrant workers can preserve sunset industries which turn protectionist. Examples from fruit and vegetable agriculture, garments, and shoes will be discussed.     

On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment

A central part of probabilistic public health risk assessment is the selection of probability distributions for the uncertain input variables. In this paper, we apply the first-order reliability method (FORM)^(1–3) as a probabilistic tool to assess the effect of probability distributions of the input random variables on the probability that risk exceeds a threshold level (termed the probability of failure) and on the relevant probabilistic sensitivities. The analysis was applied to a case study given by Thompson et al. ⁽⁴⁾ on cancer risk caused by the ingestion of benzene contaminated soil. Normal, lognormal, and uniform distributions were used in the analysis. The results show that the selection of a probability distribution function for the uncertain variables in this case study had a moderate impact on the probability that values would fall above a given threshold risk when the threshold risk is at the 50th percentile of the original distribution given by Thompson et al. ⁽⁴⁾ The impact was much greater when the threshold risk level was at the 95th percentile. The impact on uncertainty sensitivity, however, showed a reversed trend, where the impact was more appreciable for the 50th percentile of the original distribution of risk given by Thompson et al. ⁴ than for the 95th percentile. Nevertheless, the choice of distribution shape did not alter the order of probabilistic sensitivity of the basic uncertain variables.     

Bayesian adjustment for unidirectional misclassification in ordinal covariates

In this paper, we study the identification of Bayesian regression models, when an ordinal covariate is subject to unidirectional misclassification. Xia and Gustafson [Bayesian regression models adjusting for unidirectional covariate misclassification. Can J Stat. 2016;44(2):198–218] obtained model identifiability for non-binary regression models, when there is a binary covariate subject to unidirectional misclassification. In the current paper, we establish the moment identifiability of regression models for misclassified ordinal covariates with more than two categories, based on forms of observable moments. Computational studies are conducted that confirm the theoretical results. We apply the method to two datasets, one from the Medical Expenditure Panel Survey (MEPS), and the other from Translational Research Investigating Underlying Disparities in Acute Myocardial infarction Patients Health Status (TRIUMPH).     

The Expression of Victory and Loss: Estimating Who’s Leading or Trailing from Nonverbal Cues in Sports

The goal of the paper was to test if humans can detect whether athletes are trailing or leading in sports based on the perception of thin slices of athletes’ nonverbal behavior. In Experiment 1, participants who were unexperienced in the respective sports watched short videos depicting basketball and table tennis players and rated whether athletes were trailing or leading. Results indicated that participants could significantly differentiate between trailing and leading athletes in both team and individual sports. Experiment 2 showed that children were also able to distinguish between trailing and leading athletes based on nonverbal behavior. Comparison with the adult results from Experiment 1 revealed that the adult ratings corresponded to a higher degree with the actual scores during the game compared to the children’s. In Experiment 3, we replicated the findings from Experiment 1 with both expert and unexperienced participants and a different set of stimuli from team handball. Both experts and unexpert participants were able to differentiate between leading and trailing athletes. Our findings are in line with evolutionary accounts of nonverbal behavior and suggest that humans display nonverbal signals as a consequence of leading or trailing which are reliably interpreted by others. By comparing this effect as a function of different age groups we provide evidence that although even young children can differentiate between leading and trailing athletes, the decoding of subtle nonverbal cues continues to develop with increasing experience and maturation processes.     

Student and faculty perceptions about mandatory influenza vaccinations on a health sciences campus

Objective: To examine the perceptions among faculty and health professional students regarding mandatory vaccination policies on a health sciences campus. Participants: A total of 296 faculty and 244 students completed surveys during Fall 2015. Methods: The online survey administered to individuals who received the influenza vaccine during the fall 2015 influenza vaccination clinic season included five items evaluating perceptions of employer mandatory vaccination requirements. Results: Chi-square analysis indicated that although faculty and students agree mandatory vaccinations in a health care environment are appropriate, faculty are more likely than students to get vaccinated in the absence of a mandate. Additionally, a small fraction of faculty would consider employment elsewhere when facing this mandate. Conclusions: Overall, faculty and students had favorable perceptions about mandatory influenza vaccine policies. Since students were less likely to be vaccinated in the absence of a mandate, education of students should be improved to support the importance of vaccinations in a health care environment.