Not without them: realising the sustainable development goals for women migrant workers

ABSTRACT

Drawing on multiple data sources, including key informant interviews, participant observation and archival study, this paper provides an analysis of the civil society’s role in foregrounding the agenda of women migrants in migration and development (M&D) fora, and reflects on its role in realising the UN Sustainable Development Goals (SDGs). Yet, the dominant narrative within the state-led Global Forum on Migration and Development (GFMD) tends to be a gender-blind migration for development approach, which emphasises national-level economic growth at the centre of migration processes, while negating the subjectivities of women migrants and neglecting their contributions to the global economy; this approach diverts attention to a narrow focus on macro-economic development through forms of financial remittances. Based on an examination of the GFMD as a site for gender mainstreaming M&D, we reflect on lessons learned as we look forward to achieving the SDGs. We argue that while the SDGs include some significant provisions for women in migration, only critical civil society advocacy and activism networked within grassroots organisations can address the structural changes necessary (such as a re-articulation of the care economy to value economic contributions of women’s reproductive work) to transform and improve the lived realities of women in migration and realise the SDGs in a manner that fosters their empowerment.     

Relating supply performance to aircraft availability

This paper describes how the effectiveness of the supply of vital repairable items for an aircraft or weapon system can be measured in terms of the expected number of aircraft grounded because of supply shortages. The properties of this measure are compared with the three alternative methods of assessing supply performance, none of which are directly aircraft or weapon system related. The present applicability of this measure to various situations at RAF Squadron and station level are discussed, together with possible future areas of application.     

Exact moments of the symmetric cubic assignment statistic

Hubert (1987Assignment Methods in Combinatorial Data Analysis) presented a class of permutation, or random assignment, techniques for assessing correspondence between general k-dimensional proximity measures on a set of “objects.” A major problem in higher-order assignment models is the prohibitive level of computation that is required. We present the first three exact moments of a test statistic for the symmetric cubic assignment model. Efficient computational formulas for the first three moments have been derived, thereby permitting approximation of the permutation distribution using well-known methods.     

Chinese grand(parenting) encourages a re-imagining of Canada's immigration regime

Canada's migration regime prioritizes the admission of young skilled immigrants while restricting elderly immigrants constructed as non-contributing dependents. We review and compare the current pathways to family reunification for elderly immigrants. Based on interviews with 16 Chinese skilled immigrant mothers and eight sponsored (grand)parents in Edmonton and Ottawa, we highlight the contributions made by elderly Chinese immigrants to social reproduction, intergenerational cultural preservation, and various forms of transnational support. We also reveal the financial and emotional costs incurred by young skilled immigrants who sought to sponsor their elderly parents for permanent residency. Based on these rich conversations, we propose two policy recommendations to reduce the pressure on sponsoring family members and create opportunities for elderly immigrants to access gainful employment.     

Search for optimal designs in a three stagenested random model

In this paper we define a class of unbalanced designs, denoted by C_k,s,t, for estimating the components of variance in a k-stage nested random effects linear model. This class contains many of the designs proposed in the literature for nested components of variance models. We focus on the three-state model and discuss the determination of locally optimal designs within this class using a systematic computer search. For large sample sizes we show that approximate optimal designs may be obtained using a limit argument combined with numerical optimization. A comparison of our designs with previously published designs suggests that, in many cases, our designs result in substantial gains in efficiency.     

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.     

Fiducial prediction intervals

This paper presents an approach for constructing prediction intervals for any given distribution. The approach is based on the principle of fiducial inference. We use several examples, including the normal, binomial, exponential, gamma, and Weibull distributions, to illustrate the proposed procedure.     

A general class of chain estimators for ratio and product of two means of a finite population

This paper proposes a class of estimators for estimating ratio and product of two means of a finite population using information on two auxiliary characters. Asymptotic expression to terms of order 0(n^-1) for bias and mean square error (MSE) of the proposed class of estimators are derived. Optimum conditions are obtained under which the proposed class of estimators has the minimum MSE. An empirical study is carried out to compare the performance of various estimators of ratio with the conventional estimators.