Who Lives in Hard-to-Count Neighborhoods

For more than 20 years the U.S. Census Bureau has engaged in work to identify local areas that are likely to be difficult to enumerate in the Decennial Census. Such areas have been labeled “Hard-to-count.” In this study I use the final Mail Return Rates from the 2010 Census to identify a group of Census Tracts that I label Hard-to-Count or HTC. Once HTC Tracts have been identified I examine the demographic characteristics and socioeconomic characteristics of the population living in the HTC Tracts and compare them the population in all Tracts. Demographic characteristics of the HTC Tracts examined here include location, age, race, and sex, along with several socioeconomic measures such as poverty and living arrangements. The distribution of characteristics for the population residing in the HTC Census Tracts is compared to the distribution for all Tracts to develop a HTC concentration ratio. The HTC Tracts are highly concentrated geographically. The 25 counties with the most HTC Tracts account for half of all HTC Tracts. Blacks, Hispanics and American Indian populations are highly concentrated in HTC Tracts. Demographic groups with the highest concentration in HTC Tracts are identified and the net undercount rates for these groups are examined. The relationship between concentration in HTC neighborhoods and Census undercount rates is mixed

Geographic Variation in 2010 U.S. Census Coverage Rates for Young Children: A Look at Counties

Data from the Census Bureau’s Demographic Analysis (DA) show there was a net undercount of almost one million children under age 5 in the 2010 Decennial Census. The net undercount for young children was more than twice as high as any other age group. Given the high net total undercount of young children it would be useful to know how this net undercount is distributed geographically. In this study, the 2010 Decennial Census county-level counts of children age 0 to 4 are compared to corresponding figures from the Census Bureau’s Vintage 2010 population estimates, to ascertain census coverage for young children. Results show that net undercount rates for young children are higher in larger counties and counties with high percentages of Black or Hispanic children but county growth rates do not seem to be related to net undercount rates for young children. Discussion explores how this information may be helpful in the 2020 Census

Differential Undercounts in the U.S. Census

This open access book describes the differences in US census coverage, also referred to as “differential undercount”, by showing which groups have the highest net undercounts and which groups have the greatest undercount differentials, and discusses why such undercounts occur. In addition to focusing on measuring census coverage for several demographic characteristics, including age, gender, race, Hispanic origin status, and tenure, it also considers several of the main hard-to-count populations, such as immigrants, the homeless, the LBGT community, children in foster care, and the disabled. However, given the dearth of accurate undercount data for these groups, they are covered less comprehensively than those demographic groups for which there is reliable undercount data from the Census Bureau. This book is of interest to demographers, statisticians, survey methodologists, and all those interested in census coverage

Are Self-Participation Rates Predictive of Accuracy in the U.S. Census?

Metrics related to the U.S. Census have been widely available for several decades but there has been a dearth of studies examining the relationship among key metrics in the Census. This paper provides empirical evidence about the link between self-participation rates and census accuracy using data from the 1990, 2000, and 2010 U.S Censuses. The preponderance of the evidence shows lower self-participation rates are highly correlated with higher net undercounts and omissions rates for key socio-demographic groups and states. Nine out of 11 correlations examined in this paper are statistically significant and in the predicted direction. One key reason self-participation rates are associated with census accuracy is the fact that the population not captured in the self-participation operation goes into the households for the Nonresponse Followup (NRFU) operation. Census Bureau data show data collected in NRFU is not as accurate as that collected in self-response. The larger the share of data collected for a population that is collected in NFRU, the lower the quality of data for that group. The connection between self-participation rates and census accuracy mean the differential self-participation rates seen in the 2020 Census suggest patterns of net Census undercounts seen in the past are likely to be seen in the 2020 Census

Differential Undercounts in the U.S. Census

This open access book describes the differences in US census coverage, also referred to as “differential undercount”, by showing which groups have the highest net undercounts and which groups have the greatest undercount differentials, and discusses why such undercounts occur. In addition to focusing on measuring census coverage for several demographic characteristics, including age, gender, race, Hispanic origin status, and tenure, it also considers several of the main hard-to-count populations, such as immigrants, the homeless, the LBGT community, children in foster care, and the disabled. However, given the dearth of accurate undercount data for these groups, they are covered less comprehensively than those demographic groups for which there is reliable undercount data from the Census Bureau. This book is of interest to demographers, statisticians, survey methodologists, and all those interested in census coverage

Two-dimensional Ising model with competing interactions and its application to clusters and arrays of π\pi-rings and adiabatic quantum computing

We study planar clusters consisting of loops including a Josephson $\pi$-junction ($\pi$-rings). Each $\pi$-ring carries a persistent current and behaves as a classical orbital moment. The type of particular state associated with the orientation of orbital moments at the cluster depends on the interaction between these orbital moments and can be easily controlled, i.e. by a bias current or by other means. We show that these systems can be described by the two-dimensional Ising model with competing nearest-neighbor and diagonal interactions and investigate the phase diagram of this model. The characteristic features of the model are analyzed based on the exact solutions for small clusters such as a 5-site square plaquette as well as on a mean-field type approach for the infinite square lattice of Ising spins. The results are compared with spin patterns obtained by Monte Carlo simulations for the 100 $\times$ 100 square lattice and with experiment. We show that the $\pi$-ring clusters may be used as a new type of superconducting memory elements. The obtained results may be verified in experiments and are applicable to adiabatic quantum computing where the states are switched adiabatically with the slow change of coupling constants.Comment: 32 pages, 22 figures, RevTe

Presence and task performance:an approach in the light of cognitive style

The paper highlights the relationship between each of four bi-polar dimensions of personality cognitive style, such as extraversion–introversion, sensing–intuition, thinking–feeling and judging–perceiving, and the level of sense of presence experienced. Findings indicate that individuals who are more sensitive, more feeling or more introverted experience a higher level of presence. While not reaching statistical significance, differing cognitive styles appear to impact on task performance. The apparent negative relationship discovered between sense of presence and task performance should be considered in the light of task characteristics. We discuss the implications of these findings and how they contribute to an understanding of the complex relationship that exists between presence and task performance and how this subsequently ought to influence the design of virtual environments

A 40-Year Cohort Study of Evolving Hypothalamic Dysfunction in Infants and Young Children (<3 years) with Optic Pathway Gliomas

Despite high survival, paediatric optic pathway hypothalamic gliomas are associated with significant morbidity and late mortality. Those youngest at presentation have the worst outcomes. We aimed to assess presenting disease, tumour location, and treatment factors implicated in the evolution of neuroendocrine, metabolic, and neurobehavioural morbidity in 90 infants/children diagnosed before their third birthday and followed-up for 9.5 years (range 0.5–25.0). A total of 52 (57.8%) patients experienced endo-metabolic dysfunction (EMD), the large majority (46) of whom had hypothalamic involvement (H+) and lower endocrine event-free survival (EEFS) rates. EMD was greatly increased by a diencephalic syndrome presentation (85.2% vs. 46%, p = 0.001)), H+ (OR 6.1 95% CI 1.7–21.7, p 0.005), radiotherapy (OR 16.2, 95% CI 1.7–158.6, p = 0.017) and surgery (OR 4.8 95% CI 1.3–17.2, p = 0.015), all associated with anterior pituitary disorders. Obesity occurred in 25% of cases and was clustered with the endocrinopathies. Neurobehavioural deficits occurred in over half (52) of the cohort and were associated with H+ (OR 2.5 95% C.I. 1.1–5.9, p = 0.043) and radiotherapy (OR 23.1 C.I. 2.9–182, p = 0.003). Very young children with OPHG carry a high risk of endo-metabolic and neurobehavioural comorbidities which deserve better understanding and timely/parallel support from diagnosis to improve outcomes. These evolve in complex, hierarchical patterns over time whose aetiology appears predominantly determined by injury from the hypothalamic tumour location alongside adjuvant treatment strategies

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Spatial and environmental drivers of macrophyte diversity and community composition in temperate and tropical calcareous rivers

The hypothesis was examined that sources of variation in macrophyte species richness (alpha-diversity: S) and community composition (“species-set”), attributable to spatial and environmental, variables, may differ in importance between tropical and temperate calcareous rivers (&gt;10 mg CaCO3 L−1). To test this hypothesis geographic, environmental, and aquatic vegetation data was acquired for 1151 sites on calcareous rivers within the British Isles, supporting 106 macrophyte species (mean S: 3.1 species per sample), and 203 sites from Zambian calcareous rivers, supporting 255 macrophyte species (mean S: 8.3 species per sample). The data were analysed using an eigenfunction spatial analysis procedure, Moran’s Eigenvector Maps (MEM), to assess spatial variation of species richness and community composition at large regional scale (&gt;105 km2: British Isles and Zambia); and at medium catchment scale (104–105 km2: British Isles only). Variation-partitioning was undertaken using multiple regression for species richness data, and partial redundancy analysis (pRDA) for community data. For the British Isles, spatial and environmental variables both significantly contributed to explaining variation in both species richness and community composition. In addition, a substantial amount of the variation in community composition, for the British Isles as a whole and for some RBUs, was accounted for by spatially-structured environmental variables. In Zambia, species richness was explained only by pure spatial variables, but environmental and spatially-structured environmental variables also explained a significant part of the variation for community composition. At medium-scale, in the British Isles, species richness was explained by spatial variables, and only for four of the six RBUs