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The demand for big data talent is rapidly increasing with the growth of the big data industry. However, there has been limited research on what employers seek in recruiting big data talent. This paper aims to apply labor market segmentation theories to the big data labor market and develop a theoretical framework to analyze the distribution of big data talent in different labor market segments. Furthermore, we develop a salary determination model to explain wage differentials. An empirical analysis is conducted using online job advertisements from a Chinese recruitment website to investigate the labor market for big data talent in China. Our findings show that there are significant differences in the demand for big data talent across different types of cities and industries. Different types of enterprises have different requirements for individual characteristics and offer various levels of big data job positions. Furthermore, our results reveal that individual, job-related and organizational characteristics are all significant predictors of salaries. These findings can provide particularly useful insights for organizations and managers in the big data industry.

Objectives To investigate several basic psychometric properties, including construct, convergent and discriminant validity, of the tablet‐based Rapid Assessment of Cognitive and Emotional Regulation (RACER) among children aged 4–6 years in Ghana. Methods We investigated whether RACER tasks administered to children in Ghana could successfully reproduce expected patterns of performance previously found in high‐income countries on similar tasks assessing inhibitory control (e.g., slower responses on inhibition trials), declarative memory (e.g., higher accuracy on previously seen items), and procedural memory (e.g., faster responses on sequence blocks). Next, we assessed the validity of declarative memory and inhibitory control scores by examining associations of these scores with corresponding paper‐based test scores and increasing child age. Lastly, we examined whether RACER was more sensitive than paper‐based tests to environmental risk factors common in low‐ and middle‐income countries (LMICs). Results Of the 966 children enrolled, more than 96% completed the declarative memory and inhibitory control tasks; however, around 30% of children were excluded from data analysis on the procedural memory task due to missing more than half of trials. The performance of children in Ghana replicated previously documented patterns of performance. RACER inhibitory control accuracy score was significantly correlated with child age (r (929) = .09, p = .007). However, our findings did not support other hypotheses. Conclusions The high task completion rates and replication of expected patterns support that certain RACER sub‐tasks are feasible for measuring child cognitive development in LMIC settings. However, this study did not provide evidence to support that RACER is a valid tool to capture meaningful individual differences among children aged 4–6 years in Ghana.

Purpose: No diagnostic tools exist for identifying social (pragmatic) communication disorder (SPCD), a new \"Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition\" category for individuals with social communication deficits but not the repetitive, restricted behaviors and interests (RRBIs) that would qualify them for a diagnosis of autism spectrum disorder (ASD). We explored the value of items from a widely used screening measure of ASD for distinguishing SPCD from typical controls (TC; Aim 1) and from ASD (Aim 2). Method: We applied item response theory (IRT) modeling to Social Communication Questionnaire--Lifetime (Rutter, Bailey, & Lord, 2003) records available in the National Database for Autism Research. We defined records from putative SPCD (n = 54), ASD (n = 278), and TC (n = 274) groups retrospectively, based on National Database for Autism Research classifications and Autism Diagnostic Interview--Revised responses. After assessing model assumptions, estimating model parameters, and measuring model fit, we identified items in the social communication and RRBI domains that were maximally informative in differentiating the groups. Results: IRT modeling identified a set of seven social communication items that distinguished SPCD from TC with sensitivity and specificity > 80%. A set of five RRBI items was less successful in distinguishing SPCD from ASD (sensitivity and specificity < 70%). Conclusion: The IRT modeling approach and the Social Communication Questionnaire--Lifetime item sets it identified may be useful in efforts to construct screening and diagnostic measures for SPCD.

Purpose: No diagnostic tools exist for identifying social (pragmatic) communication disorder (SPCD), a new Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition category for individuals with social communication deficits but not the repetitive, restricted behaviors and interests (RRBIs) that would qualify them for a diagnosis of autism spectrum disorder (ASD). We explored the value of items from a widely used screening measure of ASD for distinguishing SPCD from typical controls (TC; Aim 1) and from ASD (Aim 2). Method: We applied item response theory (IRT) modeling to Social Communication Questionnaire-Lifetime (Rutter, Bailey, & Lord, 2003) records available in the National Database for Autism Research. We defined records from putative SPCD (n = 54), ASD (n = 278), and TC (n = 274) groups retrospectively, based on National Database for Autism Research classifications and Autism Diagnostic Interview-Revised responses. After assessing model assumptions, estimating model parameters, and measuring model fit, we identified items in the social communication and RRBI domains that were maximally informative in differentiating the groups. Results: IRT modeling identified a set of seven social communication items that distinguished SPCD from TC with sensitivity and specificity > 80%. A set of five RRBI items was less successful in distinguishing SPCD from ASD (sensitivity and specificity < 70%). Conclusion: The IRT modeling approach and the Social Communication Questionnaire-Lifetime item sets it identified may be useful in efforts to construct screening and diagnostic measures for SPCD.

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition introduced a new neurodevelopmental disorder, social (pragmatic) communication disorder (SPCD), that is characterized by deficits in 4 areas of communication. Although descriptions of these areas are provided, no assessment tools for SPCD are recommended. The purpose of this study was to examine the extent to which items from measurement tools commonly used in assessing pragmatic language impairment and related disorders might be useful in assessing the characteristics of social communication that define SPCD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Based on a literature search, 594 items from assessment tools commonly used to measure social communication abilities in people with pragmatic language impairment were identified. The first author judged whether each item reflected 1, more than 1, or none of the 4 SPCD diagnostic characteristics. After a brief training process, 5 second raters independently mapped subsets of items to the 6 categories. We calculated the percentage of agreement and Cohen's kappa for each pair of raters in assigning items to categories. Percentages of agreement ranged from 76% to 82%, and Cohen's kappa values ranged from .69 to .76, indicating substantial agreement. Sources and item numbers for the 206 items that both raters assigned to the same SPCD feature are provided. These items may provide guidance in assessing SPCD and in designing standardized screening and diagnostic measures for SPCD.