Ventriloquism,racism and the politics of decoloniality in Ecuador

ABSTRACT

This article discusses two forms of discrimination against indigenous people: ventriloquism and open racism, and argues that a transition from paternalism to open intolerance has taken place in Ecuador in the context of governmental emphasis on natural resource extraction. Ventriloquism, when non-Indians speak for indigenous people, is analysed through the Sumak Kawsay (Good Living) policies of the government of Rafael Correa (2007–2017). Public racism is examined by looking at government repression against indigenous leaders and communities and Presidential speeches. The article concludes that the state’s ventriloquist and racist discourses and practices are equally rooted in the country’s colonial past. These findings are contrasted with the writings of scholars that have called the government of Mr. Correa decolonizing. The article examines the ways in which decolonial theorists informed and promoted the policies of this regime, and argues that decolonial scholars have been insufficiently self-critical and reflective of their own complicity with the state’s repressive project vis-à-vis indigenous communities.     

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Summary.  Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models , where the latent field is Gaussian, controlled by a few hyperparameters and with non-Gaussian response variables. The posterior marginals are not available in closed form owing to the non-Gaussian response variables. For such models, Markov chain Monte Carlo methods can be implemented, but they are not without problems, in terms of both convergence and computational time. In some practical applications, the extent of these problems is such that Markov chain Monte Carlo sampling is simply not an appropriate tool for routine analysis. We show that, by using an integrated nested Laplace approximation and its simplified version, we can directly compute very accurate approximations to the posterior marginals. The main benefit of these approximations is computational: where Markov chain Monte Carlo algorithms need hours or days to run, our approximations provide more precise estimates in seconds or minutes. Another advantage with our approach is its generality, which makes it possible to perform Bayesian analysis in an automatic, streamlined way, and to compute model comparison criteria and various predictive measures so that models can be compared and the model under study can be challenged.     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

Bayesian robustness of the compound Poisson distribution under bidimensional prior: an application to the collective risk model

The distribution of the aggregate claims in one year plays an important role in Actuarial Statistics for computing, for example, insurance premiums when both the number and size of the claims must be implemented into the model. When the number of claims follows a Poisson distribution the aggregated distribution is called the compound Poisson distribution. In this article we assume that the claim size follows an exponential distribution and later we make an extensive study of this model by assuming a bidimensional prior distribution for the parameters of the Poisson and exponential distribution with marginal gamma. This study carries us to obtain expressions for net premiums, marginal and posterior distributions in terms of some well-known special functions used in statistics. Later, a Bayesian robustness study of this model is made. Bayesian robustness on bidimensional models was deeply treated in the 1990s, producing numerous results, but few applications dealing with this problem can be found in the literature.     

Living a Deportation Threat: Anticipatory Stressors Confronted by Undocumented Mexican Immigrant Women

Previous sociological research shows that exposure to stress varies by individuals’ social statuses and is a central mechanism in producing mental health disparities. This line of research suggests that ethnoracial groups are more exposed to racial discrimination, thus negatively impacting their mental health. There has also been a growing literature showing how legal status impacts the mental health of immigrants and their families. However, the sociology of mental health and migration literature has largely remained disparate. This paper bridges these literatures to highlight how living a deportation threat manifests itself as an anticipatory stressor that negatively impacts undocumented Mexican migrant women’s access to resources, social relationships, and social roles. Based on 30 semi-structured in-depth interviews with undocumented Mexican immigrant women from Houston, Texas, my findings reveal living a deportation threat is a perpetual anticipatory stressor that intensifies the effects of avoiding authorities, family fragmentation, and economic uncertainty. I argue this anticipatory stressor transforms into a chronic stressor that undocumented Mexican women confront daily. By situating this study within an anti-immigrant social context, it highlights the social processes and mechanisms that exacerbate the stressors undocumented Mexican immigrant women confront.     

Getting to know reality and breaking stereotypes: the experience of two generations of working disabled women

This paper sets out the results of a Spanish study of the experience and meaning of work among disabled women of two generations, with three types of disability (physical, visual and hearing). Performing a socially recognised activity such as a job is a source of emotional welfare and self‐esteem. Moreover, it confers a certain social status. For the participants in this study the kind of work involved, whether productive, paid and ‘extra‐domestic’ or ‘reproductive’, unpaid and done at home, acquires different meanings, since for disabled women, sexist stereotypes – already more or less accentuated in the culture – social attitudes towards disability and personal factors introduce relevant differences, while leading to conflicts and dilemmas that these women have to solve. At any rate, their sense of responsibility in performing all types of work should be emphasised as evidence of their sense of independence and personal competence, forming a keystone in their construction of a sense of identity and social integration.     

FDI Determinants: Case of Romania

Even if the FDI is important for all host countries, for those in the process of transition to a market economy the FDI presence is critical under many respects. Not all transition countries benefited from the very beginning from the FDI presence. Several determinant factors explain the differences. Romania was lagging behind regarding the interest of foreign investors during the first 9–10 years of transition. The situation has improved greatly. The aim of this paper is to identify the main factors determining the evolution in the FDI/GDP (%) as proxy for the FDI evolution. To this end, we used the method of factors analyses. The four resulted determinant factors are: Market size and potential, Reform progress, Business liberalization, and Labor cost. A linear regression model expresses the connections between dependent variable and the four determinant factors. The paper concludes with certain policy implications.

Describing poverty in an ultraperipheral region: The case of the Canary Islands

Based on data from the Survey on Social Conditions in the Canary Islands of the Instituto Canario de Estadística, this study analyzes poverty in Canary households by island of residence, age, employment and the educational level of the main provider. In addition to accepted objective measures, we also estimate poverty using subjective methods, in which the poverty line is defined or obtained by the opinion of household members of their own level of poverty.     

Persistence of an exclusionary model: Inequality and segmentation in Mexican society

Beginning in the 1980s, Mexico's social and labour policies took a neoliberal turn which exacerbated inequalities, poverty and social exclusion. The change of policy course that has occurred over the past decade has so far failed to bring about a critical review of the country's economic model and its social consequences. The role of the State has been systematically cut back; social services have been outsourced to the market; and informal family‐based social protection has gained ground. Mexico's social model has thus been reduced to a system that is almost exclusively concerned with protection for those living in extreme poverty.