Reinventar un héroe: narrativas sobre los soldados rasos de la Guerra de Corea

Esta investigación se pregunta sobre las diferentes narrativas históricas que se han construido sobre la figura de los soldados rasos de la guerra de Corea, y por cómo ellos han generado estrategias en su relato que se ajustan a unos procesos históricos determinados.

Relación entre los estilos de liderazgo y los niveles de resiliencia de los subordinados

El presente documento hace un análisis de la influencia que ejercen los diferentes tipos de liderazgo, carismático y transaccional, de un directivo de una organización sobre los subordinados de la misma, que a su vez afecta positiva o negativamente el nivel de resiliencia de los mismos. De la misma forma, se ha identificado la relación que existe entre el nivel de resiliencia de los subordinados de una organización y el cumplimiento de objetivos corporativos de la misma. Todo lo anterior se justifica en la economía globalizada de la que ahora hacemos parte que obliga a las empresas a generar nuevas estrategias de competitividad dentro de ambientes turbulentos y cambiantes donde, el desarrollar y motivar el recurso humano de la organización toma importancia para la ejecución exitosa de estrategias diferenciales.

Discurso y política sobre procesos de Desarme, Desmovilización y Reintegración en Bogotá: La representación de los desmovilizados en el diario El Tiempo (2005 - 2010)

Los procesos de Desarme, Desmovilización y Reintegración (DDR) han sido tema central en la agenda pública y la forma en que los medios nos presentan a los diferentes protagonistas del conflicto, nos ha acercado a ellos y a la realidad de ese fenómeno desde una mirada en particular. En esta monografía se analiza la representación discursiva construida por el diario El Tiempo sobre procesos de DDR y sus actores protagónicos, los desmovilizados, en la ciudad de Bogotá, entre 2005 y 2010; a lo largo del texto se reflexiona sobre la influencia que puede tener el discurso de los medios de comunicación en la manera que la sociedad podría ver y responder a ese grupo social que busca reintegrarse a la vida civil. El trabajo se realiza a través de un análisis del discurso, en este caso, del discurso periodístico emitido por el diario El Tiempo y se abordan elementos de la teoría del pánico moral. La llegada constante y creciente de desmovilizados a la capital del país conllevó a que el trato que debía dársele a la situación hiciera parte de diferentes discursos políticos y mediáticos; por tanto, el discurso del diario se contrasta con la política local de atención a desmovilizados, específicamente con el "Programa de Atención al Proceso de Desmovilización y Reintegración en Bogotá (PAPDRB)", a fin de diferenciar el tratamiento que le dieron al fenómeno.

Cuerpos Intervenidos : Experiencias corporales diferenciadas de la feminidad y el cáncer de seno

Este proyecto de investigación se enfoca en estudiar la configuración de las feminidades en mujeres que han pasado por la experiencia del cáncer de seno. Teniendo en cuenta que cada una de ellas tiene una trayectoria social diferente que determina el desarrollo de la feminidad y de la experiencia de la enfermedad. La metodología que se utilizó dentro de la investigación fue de carácter etnográfico, ya que se pretendió dar cuentan de la experiencia de la enfermedad, la corporalidad y la subjetividad.

Bayesian analysis of an inverse Gaussian correlated frailty model

In survival analysis frailty is often used to model heterogeneity between individuals or correlation within clusters. Typically frailty is taken to be a continuous random effect, yielding a continuous mixture distribution for survival times. A Bayesian analysis of a correlated frailty model is discussed in the context of inverse Gaussian frailty. An MCMC approach is adopted and the deviance information criterion is used to compare models. As an illustration of the approach a bivariate data set of corneal graft survival times is analysed. (C) 2006 Elsevier B.V. All rights reserved.

A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk

Motorcyclists and a matched group of non-motorcycling car drivers were assessed on behavioral measures known to relate to accident involvement. Using a range of laboratory measures, we found that motorcyclists chose faster speeds than the car drivers, overtook more, and pulled into smaller gaps in traffic, though they did not travel any closer to the vehicle in front. The speed and following distance findings were replicated by two further studies involving unobtrusive roadside observation. We suggest that the increased risk-taking behavior of motorcyclists was only likely to account for a small proportion of the difference in accident risk between motorcyclists and car drivers. A second group of motorcyclists was asked to complete the simulator tests as if driving a car. They did not differ from the non-motorcycling car drivers on the risk-taking measures but were better at hazard perception. There were also no differences for sensation seeking, mild social deviance, and attitudes to riding/driving, indicating that the risk-taking tendencies of motorcyclists did not transfer beyond motorcycling, while their hazard perception skill did. (C) 2002 Elsevier Science Ltd. All rights reserved.

Exploring block construction and mental imagery: evidence of atypical orientation discrimination in Williams syndrome

The visuospatial perceptual abilities of individuals with Williams syndrome (WS) were investigated in two experiments. Experiment I measured the ability of participants to discriminate between oblique and between nonoblique orientations. Individuals with WS showed a smaller effect of obliqueness in response time, when compared to controls matched for nonverbal mental age. Experiment 2 investigated the possibility that this deviant pattern of orientation discrimination accounts for the poor ability to perform mental rotation in WS (Farran, Jarrold, & Gathercole, 2001). A size transformation task was employed, which shares the image transformation requirements of mental rotation, but not the orientation discrimination demands. Individuals with WS performed at the same level as controls. The results suggest a deviance at the perceptual level in WS, in processing orientation, which fractionates from the ability to mentally transform images.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Skew-normal linear calibration: a Bayesian perspective

In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd.

En studie om rehabilitering - en skamgörande process

The purpose of this essay is using theories about labeling and social bonds to study whether a measure of rehabilitation for the psychically disabled contributes to a return to a normal status as not-labeled. Partly we examine whether the activities organized by the regulation-ruled authorities during the work of rehabilitation lead to shame or pride, and partly how these activities are organized regarding the processes that lead to the emotions pride or shame among the participants. Method: qualitative semi-structured face-to-face interviews with professional rehabilitation-actors at the Public Employment Office (PEO), the Social Insurance Office (SIO), the Social Service (SOS), the Psychiatry and the Division of Labour Market (AME).Conclusions: the Psychiatry clients are treated with respect, may participate, and communication is characterized by attunement, therefore strong social bonds can be built. On the contrary, among the other examined activities, we found many elements that arouse shame. Since these are more ruled by regulations, the result is engulfment and demands on conformity, because the compromise-possibilities are almost non-existent. Psychically disabled persons are met by prejudice, ignorance, disrespect and a non-solidarity-language. To get help, the individual has to accept a label in form of a diagnosis, and this labeling leads to a negative self-image. Furthermore the psychically disabled persons are falling between two chairs because of a weak cooperation between the rehabilitation-actors. Bimodal alienation and triangulation contributes to the difficulties in cooperation.Result: the social bonds are not strong enough to achieve a rehabilitation-effect. Even if the treatment from each administrator is important, we find the explanation-level primarily in laws, rules and government, because the structure rules the rehabilitation-measures, with shame as a consequence. Since we found elements of shame institutionalized in the way of working at PEO, SIO, SOS and AME, it means that social bonds can never reach a level good enough for achieving pride and normalization from a deviance or labeled identity.