Reclaiming the future: (In)visible dirt borders in Sammy Baloji’s mining photomontages

ABSTRACT

This paper analyses how Baloji’s photographic work Essay on Urban Planning and Mémoire/Kolwezi rely on the dialectic of visibility/invisibility of mining dirt to reveal similarities as well as discrepancies between past and present in capital and labour flows. Conflating archives of humans on display and photographs of abandoned mining sites, Baloji’s figurations of mining dirt unravel how perceptions of dirt were used by the colonial system to impose geographies of exclusion that have become invisible. While they expose how postindependence Congo has failed to appropriate its resources, Baloji’s images of artisanal miners working with mining dirt further epitomise how the disposable objects (often dematerialised via the web) consumed in rich nations involve the disposable lives of workers in the Congo within material dirt borders one can no longer see.     

Testing an Integrative Contextual Career Development Model With Adolescents From High‐Poverty Urban Areas

Variations in the economic recovery rate across the United States have led to even greater chasms that separate the employed, unemployed, and underemployed (DeSilver, 2017 ). Therefore, understanding and supporting the career development of future generations is critical—especially for those who live outside the context of social privilege. The authors examined the applicability of the integrative contextual model of career development (ICM; Lapan, 2004 ) to a sample of 220 adolescents (129 boys, 91 girls) from a high‐poverty urban area. Results indicated that a canonical variate comprising foundational ICM skills (e.g., career exploration, goal setting) predicted a variate composed of ICM outcomes (e.g., self‐efficacy, vocational identity), thus supporting the usefulness of the ICM framework for this population. The skill of setting viable career goals was an especially strong predictor of outcomes. Implications for career counseling with adolescents living in high‐poverty urban areas and directions for future research are discussed.     

Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.     

Non-asymptotic sequential confidence regions with fixed sizes for the multivariate nonlinear parameters of regression

In this paper we consider a sequential design for the estimation of nonlinear parameters of regression with guaranteed accuracy. Non-asymptotic confidence regions with fixed sizes for the least squares estimates are used. The obtained confidence region is valid for finite numbers of data points when the distributions of the observations are unknown.     

Nonparametric control charts based on runs and Wilcoxon-type rank-sum statistics

In this article, we introduce three new distribution-free Shewhart-type control charts that exploit run and Wilcoxon-type rank-sum statistics to detect possible shifts of a monitored process. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of these charts is that, due to their nonparametric nature, the false alarm rate (FAR) and in-control run length distribution is the same for all continuous process distributions. Tables are provided for the implementation of the charts for some typical FAR values. Furthermore, a numerical study carried out reveals that the new charts are quite flexible and efficient in detecting shifts to Lehmann-type out-of-control situations.     

A Bayesian Approach for Analyzing Results of Vehicle Collision Tests

Certain motor vehicle safety standards stipulate a collision test speed and a set of performance criteria that vehicles must satisfy during or after the collision test. For example, Federal Motor Vehicle Safety Standard 301 requires a 30 mile per hour (mph) barrier collision and specifies a certain maximum allowable limit on the total spillage of fuel. Vehicle designs are required to meet this standard; however, when collision tests are conducted at speeds higher than the standard, vehicles do not always satisfy the performance criteria. This paper develops a mathematical model for estimating the probability of meeting the standard by using a Bayesian framework to incorporate engineering judgment with collision test results. The model is based on the idea that there are random features to a vehicle's ability to meet performance standards in a collision, especially at such elevated speeds. Example calculations are included to illustrate the estimation of the probability of meeting the standard and to compare it with a maximum likelihood approach.     

An Exploratory Study of Financial Remittances Among Non-Resident Indians in the United States

Remittances by immigrants and temporary workers of Indian origin in industrialized countries are a growing part of India’s economy. In this exploratory study we examine the social and economic characteristics affecting the remittance pattern of working households (or families) of Indian origin residing in the United States. As most previous studies have been undertaken at the macroeconomic level, our main contribution lies in identifying the household level factors that may influence remittances. Using an online and a mail-in survey of 39 households we find some of the significant factors affecting remittances. We also validate some of the remittance-related policies of the Indian government.