Humanitarian response and stress in Kenya: gendered problems and their implications

ABSTRACT

Stress-related conditions such as burnout and post-traumatic stress disorder are a growing concern in the humanitarian sector. Aid workers themselves report not only that mental health problems are common, but that the support they receive from their employers is insufficient. Problematically, the experience of the international aid worker – particularly those who are white and from the global North – is often foregrounded in explaining what constitutes stress and related mental health problems. This indicates a wider problem of what is required of ‘the perfect humanitarian’ – a personality that is gendered and racialised – and how this influences the different experiences and treatment of national and international staff from aid agencies. This article explores the organisational culture and working conditions of humanitarian settings and their impact on the mental health and well-being of staff. It argues that there is a structural dimension to stress that is less to do with external security threats and more to do with the specific infrastructure, policies, and practices of humanitarian operations, with implications for aid workers which cut across dimensions of race, gender, and nationality.     

A pool-adjacent-violators-algorithm approach to detect infinite parameter estimates in one-regressor dose–response models with asymptotes

Binary response models are often applied in dose–response settings where the number of dose levels is limited. Commonly, one can find cases where the maximum likelihood estimation process for these models produces infinite values for at least one of the parameters, often corresponding to the ‘separated data’ issue. Algorithms for detecting such data have been proposed, but are usually incorporated directly into in the parameter estimation. Additionally, they do not consider the use of asymptotes in the model formulation. In order to study this phenomenon in greater detail, we define the class of specifiably degenerate functions where this can occur (including the popular logistic and Weibull models) that allows for asymptotes in the dose–response specification. We demonstrate for this class that the well-known pool-adjacent-violators algorithm can efficiently pre-screen for non-estimable data. A simulation study demonstrates the frequency with which this problem can occur for various response models and conditions.     

Extending social security coverage to the rural sector in China

In late 2009 China launched an innovative, voluntary programme that by 2011 had extended pension coverage to 326.4 million people in the rural sector, including contributors and beneficiaries. It requires one contribution per year and provides a flat‐rate benefit and a contributions‐related benefit through a contributory individual account, with a government guarantee that the benefit will continue for life. The programme encourages participation of persons who do not pay income taxes, and thus have no tax incentive to participate, by providing substantial government subsidies. As a further incentive, old‐age benefits are provided to older parents when all their adult children participate in the contributory programme.     

Effects of attributed responsibility and response strategies on organizational reputation: A meta-analysis of situational crisis communication theory research

Scholars utilizing situational crisis communication theory (SCCT) mainly examine how attributed responsibility affects organizational reputation and how response strategies matched with the amount of attributed responsibility protect reputation. The findings on these 2 important questions have been mixed. A meta-analysis of 35 investigations from 24 studies published between January 1990 and March 2015 was conducted to explain the mixed findings and reveal average correlations. Attributed responsibility was strongly associated with reputation at –.54, and response strategies were only weakly associated with reputation at .23. Equally important, crisis vignette choice moderated the responsibility-reputation association. Crisis clusters, reputation measurements, sample choice, and crisis vignette choice moderated the match-reputation association. Theoretical, methodological, and practical implications were discussed.     

Pseudo-Bayes and pseudo-empirical Bayes estimators in randomized response sampling

In this article, new pseudo-Bayes and pseudo-empirical Bayes estimators for estimating the proportion of a potentially sensitive attribute in a survey sampling have been introduced. The proposed estimators are compared with the recent estimator proposed by Odumade and Singh [Efficient use of two decks of cards in randomized response sampling, Comm. Statist. Theory Methods 38 (2009), pp. 439–446] and Warner [Randomized response: A survey technique for eliminating evasive answer bias, J. Amer. Statist. Assoc. 60 (1965), pp. 63–69].     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.     

Testing for parameter constancy in the time series direction in panel data models

We propose tests for parameter constancy in the time series direction in panel data models. We construct a locally best invariant test based on Tanaka [Time series analysis: nonstationary and noninvertible distribution theory. New York: Wiley; 1996] and an asymptotically point optimal test based on Elliott and Müller [Efficient tests for general persistent time variation in regression coefficients. Rev Econ Stud. 2006;73:907–940]. We derive the limiting distributions of the test statistics as T→∞ while N is fixed, and calculate the critical values by applying numerical integration and response surface regression. Simulation results show that the proposed tests perform well if we apply them appropriately.     

Bayesian estimation of rare sensitive attribute

Randomized response models have been used to estimate a population proportion of a sensitive attribute. A randomized device is typically employed to protect respondent's privacy in a survey. In addition, an unrelated question is asked to improve the statistical efficiency. In this article, we propose Bayesian estimation of rare sensitive attribute using randomized response technique, which includes a rare unrelated attribute. Two cases are considered, the proportion of a rare unrelated attribute is known and unknown. A simulation study is conducted to assess the performance of the models using mean absolute error and coverage probability. The results show that the performance depends on the parameters and is robust to priors.     

Multiple-class classification: Ordinal and categorical labels

We study multiple-class classification problems. Both ordinal and categorical labeled cases are discussed. The common approaches for multiple-class classification are built on binary classifiers, in which one-versus-one and one-versus-rest are typical approaches. When the number of classes is large, then these binary-classifier-based methods may suffer from either computational costs or the highly imbalanced sample sizes in their training stage. In order to alleviate the computational burden and the imbalanced training data issue in multiple-class classification problems, we propose a method that has competitive performance and retains the ease of model interpretation, which is essential for a prognostic/predictive model.     

Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data

In this paper, a competing risks model is considered under adaptive type-I progressive hybrid censoring scheme (AT-I PHCS). The lifetimes of the latent failure times have Weibull distributions with the same shape parameter. We investigate the maximum likelihood estimation of the parameters. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) techniques to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, a simulation study is carried out.