Disparate Measures Research Articles

Person Re-Identification Using Deep Learning Approach: A Survey

Person Re-identification proof crosswise over various observation cameras with disjoint fields of view has turned out to be one of the most intriguing and testing subjects in the zone of wise video observation. Albeit a few techniques have been created, what's more, proposed, certain confinements and uncertain issues remain. In the majority of the current Re-identification proof approaches, highlight vectors are separated from sectioned still pictures or video outlines. Distinctive similitude or disparity measures have been applied to these vectors. A few strategies have utilized basic consistent measurements, while others have used models to acquire streamlined measurements. Some have made models dependent on neighborhood shading or surface data, and others have constructed models dependent on the stride of individuals. When all is said in done, the primary goal of every one of these methodologies is to accomplish a higher-exactness rate and lower computational costs.

U.S. Infant Mortality Rates: An Exploration of Black/White Disparities, Current Trends, and Social Inequalities

The purpose of this paper is to explore 10-year trends in infant mortality rates (IMRs) from 2007 to 2016 for non-Hispanic (NH) blacks and NH whites by levels of sociodemographic characteristics such as maternal age, marital status, education, and access to prenatal care. Using data from the Centers for Disease Control and Prevention (CDC) Wonder Online database, descriptive statistics were performed, and a measure of disparity was calculated to illustrate racial differences in IMRs. Between 2007 and 2016, IMRs for NH blacks have declined at a faster rate (15.8%) compared to NH whites (13.5%). As for the selected sociodemographic indicators, reductions were observed for both racial groups for most age categories assessed, married and unmarried women, and for women with early or no access to prenatal care. For educational attainment levels, declines were observed for both racial groups for all levels except for high school graduate or GED and some college, in which increases were observed for NH white women. The measure of disparity illustrates the large racial gap in IMRs persists between NH blacks and NH whites. More structural and systemic mechanisms, including research and policies, are needed to address the disparities in IMRs.

Firearm homicide mortality is influenced by structural racism in US metropolitan areas.

Metropolitan cities in the United States suffer from higher rates of gun violence. However, the specific structural factors associated with increased gun violence are poorly defined. We hypothesized that firearm homicide in metropolitan cities would be impacted by Black-White segregation index. This cross-sectional analysis evaluated 51 US metropolitan statistical areas (MSAs) using data from 2013 to 2017. Several measures of structural racism were examined, including the Brooking Institute's Black-White segregation index. Demographic data were derived from the US Census Bureau, US Department of Education, and US Department of Labor. Crime data and firearm homicide mortality rates were obtained from the Federal Bureau of Investigation and the Centers for Disease Control. Spearman ρ and linear regression were performed. Firearm mortality was associated with multiple measures of structural racism and racial disparity, including White-Black segregation index, unemployment rate, poverty rate, single parent household, percent Black population, and crime rates. In regression analysis, percentage Black population exhibited the strongest association with firearm homicide mortality (β = 0.42, p < 0.001). Black-White segregation index (β = 0.41, p = 0.001) and percent children living in single-parent households (β = 0.41, p = 0.002) were also associated with higher firearm homicide mortality. Firearm legislation scores were associated with lower firearm homicide mortality (β = -0.20 p = 0.02). High school and college graduation rates were not associated with firearm homicide mortality and were not included in the final model. Firearm homicide disproportionately impacts communities of color and is associated with measures of structural racism, such as White-Black segregation index. Public health interventions targeting gun violence must address these systemic inequities. Furthermore, given the association between firearm mortality and single-parent households, intervention programs for at-risk youth may be particularly effective. Epidemiological level II.

Cumulative residual extropy of minimum ranked set sampling with unequal samples

Recently, an alternative measure of uncertainty called cumulative residual extropy (CREX) was proposed by Jahanshahi et al. (2019). In this paper, we consider uncertainty measures of minimum ranked set sampling procedure with unequal samples (MinRSSU) in terms of CREX and its dynamic version and we compare the uncertainty and information content of CREX based on MinRSSU and simple random sampling (SRS) designs. Also, using simulation, we study new estimators of CREX for MinRSSU and SRS designs in terms of bias and mean square error. Finally, we provide a new discrimination measure of disparity between the distribution of MinRSSU and parental data SRS.

Health, Longevity, and Welfare Inequality of Older Americans

We estimate the distribution of well-being among the older U.S. population using an expected utility framework that incorporates differences in consumption, leisure, health, and mortality. We find large disparities in welfare that have increased over time. Incorporating the cost of living with poor health into elderly welfare substantially increases the overall inequality. Disparity measures based on cross-sectional income or consumption underestimate the growth in aggregate welfare inequality. Moreover, health is a better indicator of an individual’s relative welfare position than income or consumption.

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

The increasing impact of algorithmic decisions on people’s lives compels us to scrutinize their fairness and, in particular, the disparate impacts that ostensibly color-blind algorithms can have on different groups. Examples include credit decisioning, hiring, advertising, criminal justice, personalized medicine, and targeted policy making, where in some cases legislative or regulatory frameworks for fairness exist and define specific protected classes. In this paper we study a fundamental challenge to assessing disparate impacts in practice: protected class membership is often not observed in the data. This is particularly a problem in lending and healthcare. We consider the use of an auxiliary data set, such as the U.S. census, to construct models that predict the protected class from proxy variables, such as surname and geolocation. We show that even with such data, a variety of common disparity measures are generally unidentifiable, providing a new perspective on the documented biases of popular proxy-based methods. We provide exact characterizations of the tightest possible set of all possible true disparities that are consistent with the data (and possibly additional assumptions). We further provide optimization-based algorithms for computing and visualizing these sets and statistical tools to assess sampling uncertainty. Together, these enable reliable and robust assessments of disparities—an important tool when disparity assessment can have far-reaching policy implications. We demonstrate this in two case studies with real data: mortgage lending and personalized medicine dosing. This paper was accepted by Hamid Nazerzadeh, Management Science Special Section on Data-Driven Prescriptive Analytics.

Private health care market shaping and changes in inequities in childhood diarrhoea treatment coverage: evidence from the analysis of baseline and endline surveys of an ORS and zinc scale-up program in Nigeria

BackgroundNearly 90,000 under-five children die from diarrhoea annually in Nigeria. Over 90% of the deaths can be prevented with oral rehydration salt (ORS) and zinc treatment but coverage nationally was less than 34% for ORS and 3% for zinc with wide inequities. A program was implemented in eight states to address critical barriers to the optimal functioning of the health care market to deliver these treatments. In this study, we examine changes in the inequities of coverage of ORS and zinc over the intervention period.MethodsBaseline and endline household surveys were used to measure ORS and zinc coverage and household assets. Principal component analysis was used to construct wealth quintiles. We used multi-level logistic regression models to estimate predictive coverage of ORS and zinc by wealth and urbanicity at each survey period. Simple measures of disparity and concentration indices and curves were used to evaluate changes in ORS and zinc coverage inequities.ResultsAt baseline, 28% (95% CI: 22–35%) of children with diarrhoea from the poorest wealth quintile received ORS compared to 50% (95% CI: 52–58%) from the richest. This inequality reduced at endline as ORS coverage increased by 21%-points (P < 0.001) for the poorest and 17%-points (P < 0.001) for the richest. Zinc coverage increased significantly for both quintiles at endline from an equally low baseline coverage level. Consistent with the findings of the pairwise comparison of the poorest and the richest, the summary measure of disparity across all wealth quintiles showed a narrowing of inequities from baseline to endline. Concentration curves shifted towards equality for both treatments, concentration indices declined from 0.1012 to 0.0480 for ORS and from 0.2640 to 0.0567 for zinc. Disparities in ORS and zinc coverage between rural and urban at both time points was insignificant except that the use of zinc in the rural at endline was significantly higher at 38% (95%CI: 35–41%) compared to 29% (95%CI, 25–33%) in the urban.ConclusionThe results show a pro-rural improvement in coverage and a reduction in coverage inequities across wealth quintiles from baseline to endline. This gives an indication that initiatives focused on shaping healthcare market systems may be effective in reducing health coverage gaps without detracting from equity as a health policy objective.

Pathways Through Juvenile Justice: A System-Level Assessment of Cumulative Disadvantage in the Processing of Juvenile Offenders

To test the cumulative disadvantage hypothesis—that system-level racial and ethnic disparities accumulate from intake to final disposition—by investigating relative and absolute disparities across different pathways through the juvenile justice system. Using a sample of 95,670 juvenile court referrals across 140 counties in four states, the present study employed multinomial logistic regression to examine racial and ethnic disparities across 14 possible combinations of juvenile justice outcomes (i.e., pathways), ranked from least to most punitive. We then estimated predicted probabilities and marginal effects of race and ethnicity for each pathway. We found limited support for the cumulative disadvantage hypothesis. Racial and ethnic disparities were greatest for the most punitive pathways, but the findings do not point to extensive evidence of cumulative disadvantage. Specifically, neither relative nor absolute disparities accumulated from least to most punitive pathways, and some of the least punitive pathways were actually more likely for minority defendants. The results underscore the need for more careful measurement and analysis of disadvantage and disparities in the criminal and juvenile justice systems. In particular, more attention should be paid to early outcomes such as detention, where large differences between racial and ethnic groups were observed, as well as to relative and absolute differences in processing outcomes.

Resiliency to adversity in military personnel: The role of self-regulation

ABSTRACT Military service can include numerous adverse events. As such, resiliency has been considered as a means of potentially helping active-duty personnel face adversity and be better prepared for the demands of military service. However, research in military contexts has been hindered by use of disparate conceptualizations, definitions, and measures of resiliency. To provide some resolution to these inconsistencies, we use a comprehensive, theoretically based model of resiliency to explore how self-regulation processes contributed to Soldiers’ negative affect and self-perceived effectiveness. We hypothesized that self-regulation (comprising distinct affective, behavioral, and cognitive processes) increments prediction of Soldiers’ outcomes over and above trait-based resiliency protective factors. Using a sample of active-duty military personnel, cognitive self-regulation and affective self-regulation incremented the prediction of negative affect and self-perceived Soldier effectiveness, respectively, over and above trait-based protective factors. These results support the use of a comprehensive model and measure of resiliency, which may enable greater consistency across future research endeavors. As these results validated the links between self-regulation and post-adversity outcomes, this study provides a basis for developing new resiliency training programs. Additional implications for theory and continued research on resiliency in military contexts are discussed.

Generalised Informative Discrimination Measure and Its Properties with Applications

The Shannon interval uncertainty was suggested as a convenient functional uncertainty metric for dual-sided shortened latent variables in the composite reliability. A new measure of disparity has recently been suggested between two doubly truncated distributions of life. The generalised informative discrimination measure for lifetime distribution in the given time interval is described in the present paper. Few features of the new generalised measure are also being investigated. An analysis of lung-cancer data is done using survival function, and Kaplan Meier estimator using Python libraries.

Structural Racism and COVID-19 in the USA: a County-Level Empirical Analysis.

Substantial health disparities exist across race/ethnicity in the USA, with Black Americans often most affected. The current COVID-19 pandemic is no different. While there have been ample studies describing racial disparities in COVID-19 outcomes, relatively few have established an empirical link between these disparities and structural racism. Such empirical analyses are critically important to help defuse “victim-blaming” narratives about why minority communities have been badly hit by COVID-19. In this paper, we explore the empirical link between structural racism and disparities in county-level COVID-19 outcomes by county racial composition. Using negative binomial regression models, we examine how five measures of county-level residential segregation and racial disparities in socioeconomic outcomes as well as incarceration rates are associated with county-level COVID-19 outcomes. We find significant associations between higher levels of measured structural racism and higher rates of COVID-19 cases and deaths, even after adjusting for county-level population sociodemographic characteristics, measures of population health, access to healthcare, population density, and duration of the COVID-19 outbreak. One percentage point more Black residents predicted a 1.1% increase in county case rate. This association decreased to 0.4% when structural racism indicators were included in our model. Similarly, one percentage point more Black residents predicted a 1.8% increase in county death rates, which became non-significant after adjustment for structural racism. Our findings lend empirical support to the hypothesis that structural racism is an important driver of racial disparities in COVID-19 outcomes, and reinforce existing calls for action to address structural racism as a fundamental cause of health disparities.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40615-020-00948-8.

The DOOR to Antibiotic Stewardship: Refining Assessments of Interventions With Desirability of Outcome Ranking

Background: Limited sample size and disparate outcome measures can hinder the ability of antimicrobial stewardship programs to assess the utility of their quality improvement interventions. Desirability of outcome ranking (DOOR) is a novel methodology that incorporates multiple outcomes into a single value to more comprehensively compare therapeutic strategies. The objective of this study was to apply DOOR to a single center antibiotic stewardship intervention. Methods: A pre- and post-interventional study was conducted evaluating the impact of prospective pharmacist review of rapid molecular diagnostic testing (RDT) of blood cultures on antibiotic optimization. Outcomes included the percentage of patients who were switched to appropriate therapy, the time to appropriate therapy, and the percentage of patients who had missed de-escalation opportunities. Results: A total of 19 and 29 patients were included in the final analysis. The percentage of patients reaching appropriate therapy was 84% (16/19) and 97% ([28/29], p = 0.16) in the pre-intervention and post-intervention groups respectively. Median time to appropriate therapy was 26 hours and 36 minutes (IQR 13:05-50:45) and 22:40 (IQR 3:42-48:23, p = 0.32), respectively. One missed de-escalation opportunity was identified in the post-intervention group (0% vs 3%, p = 1.00). DOOR analysis indicated that the probability of a better outcome for the post-intervention group than the pre-intervention group was 58% (95% CI 54-62). Conclusion: In this analysis, DOOR revealed a benefit that would not have been apparent with traditional outcomes assessments. Antimicrobial stewardship programs conducting quality improvement studies should consider incorporating DOOR into their methodology.

The Construction of an Asset Index at Household Level and Measurement of Economic Disparities in Punjab (Pakistan) by using MICS-Micro Data

The main objectives of this study are to construct a valid and reliable asset index at household level and to estimate economic disparities in 36 districts of Punjab (Pakistan) by using Multiple Indicator Cluster Survey micro-data. An asset index may be a better measure than current income or expenditure for gauging a household’s long-term capacity for buying goods and services and its potential resilience to economic shocks. This paper provides details of the results from Exploratory Factor Analysis (EFA) and Tetrachoric Principal Component Analysis (PCA) for the dimensional structure of assets. We have applied Classical Test Theory (CTT) and Item Response Theory (IRT) in order to construct a reliable household level asset index. In Punjab, Lahore has the highest asset index score followed by Gujrat and Sialkot. Gini-coefficient index and the Palma ratio analyses show that the asset distribution in the district of Rajanpur is highly unequal.

Equal Protection Under the Law: The Measurement of Structural Racism and Health Disparities

Equal Protection Under the Law: The Measurement of Structural Racism and Health Disparities

How Did the Covid-19 Crisis Affect Different Types of Workers in the Developing World?

This paper investigates the impacts of the economic shock caused by the COVID-19 pandemic on the employment of different types of workers in developing countries. Employment outcomes are taken from a set of high-frequency phone surveys conducted by the World Bank and National Statistics Offices in 40 countries. Larger shares of female, young, less educated, and urban workers stopped working. Gender gaps in work stoppage were particularly pronounced and stemmed mainly from differences within sectors rather than differential employment patterns across sectors. Differences in work stoppage between urban and rural workers were markedly smaller than those across gender, age, and education groups. Preliminary results from 10 countries suggest that following the initial shock at the start of the pandemic, employment rates partially recovered between April and August, with greater gains for those groups that had borne the brunt of the early jobs losses. Although the high-frequency phone surveys greatly over-represent household heads and therefore overestimate employment rates, case studies in five countries suggest that they provide a reasonably accurate measure of disparities in employment levels by gender, education, and urban/rural location following the onset of the crisis, although they perform less well in capturing disparities between age groups. These results shed new light on the labor market consequences of the COVID-19 crisis in developing countries, and suggest that real-time phone surveys, despite their lack of representativeness, are a valuable source of information to measure differential employment impacts across groups during a crisis.

On the actual problems of managing the processes of transformation and development of rural territories of the Khabarovsk Krai

The article discusses the current problems of transformation of rural areas of the southern Khabarovsk region. It is noted that despite the current State program of the Russian Federation “Complex Rural Development”, it was not possible to stop the migration outflow of people from rural areas of this districts. There are not enough disparate measures to improve rural settlements, and a well-thought-out scientifically sound and financially secure strategy for the development of Far Eastern villages is needed.

Prerequisites for innovative development of the economy

The article focuses on the importance of innovative development of Ukraine's economy. It is emphasized that although the apopheme "innovative development" has become a stamp of public speaking in recent years, in reality it is only a flair that unsuccessfully covers disparate activities that a priori can not ensure success in this direction. It is emphasized that only a methodological substantiation of the possibilities of innovative economic development can ensure the development of its strategy, as the current disparate measures have not provided comprehensive success not only in Ukraine but also in post-socialist countries in general. On the basis of statistical indicators, there are doubts about the hopes for innovative economic development due to increased production of certain types of export-oriented agricultural products, as this is accompanied by population decline, mainly rural, and even the disappearance of rural settlements. After all, due to the concentration of exports mainly on a limited number of commodities - agricultural products and base metals - ie with low added value, foreign exchange earnings from which do not compare with the cost of imported innovative means of production, opportunities for innovative development are limited, as other companies mostly buy second-hand cars, such as cars, tractors, combines, metalworking machines, etc., as new ones are not available to most of them due to the price factor. The error of combining the accounting of antipodic categories on one account 13 "Depreciation (amortization) of non-current assets" is indicated, which to some extent led to the futility of calculations for the integrated implementation of cyber systems in all business processes (digitalization, artificial intelligence, robotics, development of circular economy and green energy, the use of new materials and passive monitoring of the growth of depreciation of fixed assets in almost all sectors of material production, as well as its statistical adjustment in the direction of leveling due to the roll of control over the reliability of reporting towards fiscal and the need to focus the efforts of the administrative community and scientists on the analytical understanding of the problem of innovative economic development in order to methodologically substantiate the real way of its implementation.

The Scientometric Measurement of Interdisciplinarity and Diversity in Research Portfolios of Chinese Universities

Purpose: “Interdisciplinarity” is a hot topic in science- and technology-policy. However, the concept of “Interdisciplinarity” is both abstract and complex, and therefore difficult to measure using a single indicator. A variety of measures for diversity and interdisciplinarity have been proposed in the literature. Can one rank institutions in terms of their (inter )disciplinary diversity? Design/methodology/approach: We developed a routine (interd_vb.exe ) which outputs for any data matrix the values of the advanced diversity diversity indicators Rao-Stirling (RS) diversity and DIV*, as well as standard measures of diversity such as the Gini coefficient, the Shannon entropy, and the Simpson Index. As an empirical example, we compare the research portfolios of 42 “Double First-Class” Chinese universities in terms of Web-of-Science Subject Categories (WCs). Findings: The empirical results suggest that DIV* provides results which are in line with intuitive impressions more than RS, particularly when the results are based on sample-dependent disparity measures. Diversity values based on a global disparity matrix are more consistent than the results based on a local map. Research limitations: “Interdisciplinarity” can be operationalized as bibliographic coupling among (sets of) documents with references to disciplines. Diversity at the institutional level, however, may also indicate comprehensiveness. Different from impact (e.g., citation), diversity and interdisciplinarity are context-specific and thus provide a different (that is, second) dimension to the evaluation. Policy or practical implications: Operationalization and quantification force the analyst to make one’s choices and options clear. Although the equations of diversity indicators are often mathematically transparent, the specification in terms of computer code helps the analyst to further precision in decisions. Furthermore, our empirical results indicate that universities do not tend to isomorphism in this second dimension. Although diversity is not necessarily a goal of universities, a high value of diversity may support potential policies of interdisciplinarity at the university level. Originality/value: We introduce a non-commercial application in the public domain enabling researchers and policy analysts to measure “diversity” and “interdisciplinarity” using the various indicators as encompassing as possible for any document set or network structure (e.g., a network of co-authors). Insofar as we know, such a professional computing tool to evaluate data sets using diversity indicators has not yet been made available online.

Surface slant impairs disparity discontinuity discrimination

Binocular disparity signals are highly informative about the three-dimensional structure of visual scenes, including aiding the detection of depth discontinuities between surfaces. Here, we examine factors affecting sensitivity to such surface discontinuities. Participants were presented with random dot stereograms depicting two planar surfaces slanted in opposite directions and were asked to judge the sign of the depth discontinuity created where those surfaces met. Although the judgement was focussed on the adjacent edges, the precision of depth discontinuity discrimination depended upon the slant of the two surfaces: increasing surface slants to ±60° increased discontinuity discrimination thresholds by, on average, a factor of 5. Control experiments examining discontinuity discrimination across surfaces with identical slants showed either biases in discontinuity judgements or reduced threshold elevation. These results suggest that sensitivity to depth discontinuities is affected by processing limitations in both local absolute disparity measurement mechanisms and mechanisms selective for disparity differences. As further evidence in support of this conclusion, we show that our results are well-described by a model of discontinuity discrimination based on the encoding of local differences in relative disparity.

The ratio of expansion to compression: A new measure of lifespan disparity.

Numerous studies have shown that high life expectancy is closely related to low life disparity. Unlike life expectancy, which can be increased by mortality decline at any age, life disparity can either increase or decrease in response to mortality decline. Disparity can thus be decomposed into two opposite components, called compression and expansion, depending on the effect of mortality decline on the age distribution of mortality. Without specifying the two components, various conventional measures of disparity may provide misleading information relating to how life chances in society can be equalized. Based on the relevant properties of changes in disparity, we develop a new measure of disparity-the ratio of expansion to compression-that can account for the relative importance of the two components. This simple measure not only provides a clear view of the evolution of disparity, but also permits changes in disparity related to mortality decline to be interpreted in a consistent manner similar to life expectancy. Simulations and an empirical analysis demonstrated the advantages of this new measure over conventional measures of disparity.