Comparing Nonparametric Estimators for Length-Biased Data

Length-biased data appear when sampling lifetimes by cross-section. Right-censoring may affect the sampled information due to time limitation in following-up, lost to follow-up cases, etc. In this article, we compare by simulations two alternative nonparametric estimators of the lifetime distribution function when the data are length-biased and right-censored. These estimates, recently introduced in the literature, are based on nonparametric maximum-likelihood and moment-based principles. It is shown that the relative benefits associated to each estimator depend on several factors, such as the shape of the underlying distribution, sample size, or censoring level.     

Sensitivity analysis in multivariate methods: Decomposition of an arbitrary influence into a finite number of components

The influence function of the covariance matrix is decomposed into a finite number of components. This decomposition provides a useful tool to develop efficient methods for computing empirical influence curves related to various multivariate methods. It can also be used to characterize multivariate methods from the sensitivity perspective. A numerical example is given to demonstrate efficient computing and to characterize some procedures of exploratory factor analysis.     

On limiting behavior for arrays of rowwise negatively orthant dependent random variables

In this paper, the authors study limiting behavior for arrays of rowwise negatively orthant dependent random variables and obtain some new results which extend and improve the corresponding theorems by Hu, Móricz, and Taylor (1989), Taylor, Patterson, and Bozorgnia (2002) and Wu and Zhu (2010).     

A Bayesian Analysis of Directional Data Using the von Mises–Fisher Distribution

ABSTRACT

This article presents a Bayesian analysis of the von Mises–Fisher distribution, which is the most important distribution in the analysis of directional data. We obtain samples from the posterior distribution using a sampling-importance-resampling method. The procedure is illustrated using simulated data as well as real data sets previously analyzed in the literature.     

Language in the process of labour market rationalisation: A sociohistorical approach across twentieth-century Spain

This article analyses the role of linguistic skills in the process of defining professional classifications in Spain during 1919–1980. The aim is to determine the social evaluation of the skills involved. To retrace the classifications, a total of 114 official documents were examined, establishing a chronological division into three major stages: 1920–1940, 1940–1960 and 1960–1980. The first period (1920–1940) shows efforts toward the initial objectification of working conditions and salary scales, revealing social prejudices and tacit conventions shaping the employment hierarchy, while the second one (1940–1960) indicates the extent to which office work stood out over manual work. Finally, the third stage (1960–1980) shows processes of language rationalisation, which entailed attempts to standardise positions based on required skill sets.     

Caseworkers as a source of hope leading to perceptions of academic success for transitional age foster youth

Research among adolescent samples has consistently demonstrated that a hopeful mindset is associated with resilience and global well-being. Further, research suggests that hope is influenced from an early age from connections with supportive caregivers. However, because older youth in the child welfare system may lack supportive caregivers, alternative sources of hope may be needed. To test a theory that supportive child welfare caseworkers can serve as external sources of hope, we conducted a cross-sectional study of youth in the child welfare system from a single state (N = 149). Using surveys with established scales to measure the variables of interest, the study tested a structural equation model of (1) youth's external hope in their caseworker as a driver of (2) internal hope in themselves leading to (3) more positive perceptions of academic success. Perceptions of academic success were chosen as the final consequence of the model because academic success has been linked to many other variables of well-being across the lifespan. The results indicate that the proposed structural model fits the data well (χ² = 327.9, df = 150; P < 0.001; root-mean-square error of approximation [RMSEA] = 0.09 [90% confidence interval – CI: 0.076, 0.103]; comparative fit index [CFI]: 0.920; standardized root-mean-square residual [SRMR]: 0.05). The results indicate that youths' hope in themselves had origins in external hope in the caseworker. Moreover, the final consequence was an increase in perceptions of academic success. Such results have implications by revealing how case management services can positively influence foster youths' hope and thereby influence their academic success.     

Avian species richness in cities: A review of the Spanish-language literature from the Southern Cone of South America

Urban Ecosystems - South America sustains an important part of the world’s terrestrial biodiversity and its population is highly urbanized. Global syntheses have revealed a paucity of urban...     

Free time,gender and the pandemic: An exploration of children's daily routines in the times of COVID-19 in Chile

This article discusses the differentiation by gender displayed by children between 8 and 12 years old on how they used their free time during the COVID-19 pandemic in Chile. This study had a qualitative approach, where 43 in-depth interviews were conducted with children from three different regions of the country, using participatory photo-elicitation as the central tool. The main results of the study show a configuration of free time based on gender stereotypes, showing that boys are the ones who most adhere to such stereotypes, triggering a crisis in the identity construction of masculinities during childhood. The study also suggests that socioeconomic and territorial differences between children configures different experiences of the use of free time.     

Classification Algorithm for Skin Color (CASCo): A new tool to measure skin color in social science research

Objective

A growing body of literature reveals that skin color has significant effects on people's income, health, education, and employment. However, the ways in which skin color has been measured in empirical research have been criticized for being inaccurate, if not subjective and biased.

Objective

Introduce an objective, automatic, accessible and customizable Classification Algorithm for Skin Color (CASCo).

Methods

We review the methods traditionally used to measure skin color (verbal scales, visual aids or color palettes, photo elicitation, spectrometers and image-based algorithms), noting their shortcomings. We highlight the need for a different tool to measure skin color

Results

We present CASCo, a (social researcher-friendly) Python library that uses face detection, skin segmentation and k-means clustering algorithms to determine the skin tone category of portraits.

Conclusion

After assessing the merits and shortcomings of all the methods available, we argue CASCo is well equipped to overcome most challenges and objections posed against its alternatives. While acknowledging its limitations, we contend that CASCo should complement researchers. toolkit in this area.