L1 mediation in Chinese English learners’ mental lexicon: Evidence from word association tests

The study aimed to explore the evidence of first language (L1) mediation in second language (L2) word associations and the L2 learner-related factors affecting the extent of L1 mediation with the following approaches. First, different from previous research, word association tests (WATs) embraced both receptive and productive word associations in the study. Second, different from word-related variables such as cognates vs. non-cognates in previous research, the study examined learner-related factors. Third, it examined whether the methodological difference (receptive vs. productive test formats) may affect the extent of L1 mediation in L2 access. A total of 108 Chinese English learners varying in proficiency, learning experiences, input and motivation participated in WATs using 24 stimulus words. The results suggested, (1) from the findings of descriptive statistics and ANOVAs, the evidence of L1 mediation was found in all three L2 proficiency groups with different extent of higher L1 mediation in lower proficiency groups. (2) From the findings of Pearson product-moment correlation coefficients, significant correlations were found with L1-promoting learning environments, L2 input, integrative motivation and the learners’ awareness of L1 activation. (3) The findings of the paired-samples t-tests confirmed a significant difference between the two test formats. Based on the findings, the study suggested the promotion of L2-rich learning environments, integrative motivation, and receptive and productive word associations in the L2 network.

BISoN: A Bayesian Framework for Inference of Social Networks

Social networks are often constructed from point estimates of edge weights. In many contexts, edge weights are inferred from observational data, and the uncertainty around point estimates can be affected by various factors. Though this has been acknowledged in previous work, methods that explicitly quantify uncertainty in edge weights have not yet been widely adopted, and remain undeveloped for common types of data. Furthermore, existing methods are unable to cope with some of the complexities often found in observational data, and do not propagate uncertainty in edge weights to subsequent analyses. We introduce a unified Bayesian framework for modelling social networks based on observational data. This framework, which we call BISoN, can accommodate many common types of observational social data, can capture confounds and model effects at the level of observations, and is fully compatible with popular methods of social network analysis. We show how the framework can be applied to common types of data and how various types of downstream analyses can be performed, including non-random association tests and regressions on network properties. Our framework opens up the opportunity to test new types of hypotheses, make full use of observational datasets, and increase the reliability of scientific inferences. We have made example R code available to enable adoption of the framework.

Hospice Care Inequities in Individuals With Alzheimer's Disease and Related Dementias

Despite known benefits of hospice, inequities exist. Using data from a multi-site pragmatic trial in a representative groups of hospices, we examined inequities in length of stay (LOS) and general inpatient use (GIU) for 12,153 patients with dementia (primary and secondary diagnosis) using descriptive statistics and association tests. There were significant associations between race/ethnicity and GIU and LOS (p< 0.001). In those with primary diagnosis of dementia, Asian (31%) and Black/AA (24%) individuals had significantly greater utilization of GIU than Hispanic (19%) and white individuals (21%). Greater inequities were found in those with a secondary diagnosis. LOS amongst Asians were shortest with 78% having an LOS ≦14 vs 50-59% in other groups. Differences in long-stay >60 days (7%) vs 14-22% in other groups were found. There were similar differences examining by primary vs. secondary diagnosis. These inequities point to cultural and systems factors that require further study and intervention.

Investigating the Structure of Son Bias in Armenia With Novel Measures of Individual Preferences

Sex ratios at birth favoring boys are being documented in a growing number of countries, a pattern indicating that families selectively abort females. Son bias also explains why, in many countries, girls have more siblings and are born at relatively earlier parities compared with their brothers. In this study, we develop novel methods for measuring son bias using both questionnaire items and implicit association tests, and we collect data on fertility preferences and outcomes from 2,700 participants in Armenia. We document highly skewed sex ratios, suggesting that selective abortions of females are widespread among parents in our sample. We also provide evidence that sex-selective abortions are underreported, which highlights the problem of social desirability bias. We validate our methods and demonstrate that conducting implicit association tests can be a successful strategy for measuring the relative preference for sons and daughters when social desirability is a concern. We investigate the structure of son-biased fertility preferences within households, across families, and between regions in Armenia, using measures of son bias at the level of the individual decision-maker. We find that men are, on average, considerably more son-biased than women. We also show that regional differences in son bias exist and that they appear unrelated to the socioeconomic composition of the population. Finally, we estimate the degree of spousal correlation in son bias and discuss whether husbands are reliably more son-biased than their wives.

The language ability, speech competence, speech activity of Generation Z

The paper aims to demonstrate possible approaches to solving problems arising during comprehensive linguistic description of the language ability, speech competence, speech activity of Generation Z. This purpose was achieved with the help of evaluation of speech acts performed in the process of associating and in the course of spontaneous connected written speech activity. Material: the results of free and directed pair by association tests conducted by the author in 2010–2012, 2015–2016, 2019–2021. Additionally, essay texts about the topics «I and the world around me», «If it were not for computers and tablet computers», «My city» («What places in Omsk do I like to visit? Why? «), «Who do I want to resemble?», «An elderly person. What is he / she like?», «Old age. What is it like? «, «In my old age I will…», «Happiness… as I understand it» were used. The essays were written by school students of the 7th, 8th and 9th forms in 2005, 2010, 2015–2016, 2020. Methods: free and directed pair by association experiments, comprehensive text analysis. The latter enabled the author to define the following parameters: communicative (speech strategies and tactics, communication types), cognitive (actualisation of meanings and cognitive structures), semantic (word selection, distribution of object features, identification of predicates and so on), statistical (the number of words per sentence and sentences per text). The results of the study: specific features of speech actions during free and directed pair by association tests were determined. Additionally, the research revealed that Generation Z members use slang verbal and graphic signs; typical scenarios caused by certain cognitive fragments which are present in their linguistic consciousness prevail. Conclusions: I-to-subject communication is the key means for organising narration, and it dominates the communicative organisation of connected texts independent of the topic. Semantic text development is based on the form and contents of the title and virtually follows it in the reactive dialogical mode. Introductions and conclusions in the essays are reduced. At the informational level, conceptual information outweighs factual and directly develops the thesis implied in the title. The variety of semantic, conceptual, cognitive features of the texts is limited; the essays are devoid of conceptual multiple layers. The development level of teenagers’ discursive thinking, in particular, inadequate development of speech activity determines their mastering of the format of a cohesive speech piece. This is shown in organisational simplicity and insufficient text volume; cohesion is achieved with the help of lexical and syntactic repetition. In the process of written speech, the types of performed speech actions aimed to verbalise meanings are connected with the reproduction of cognitive scenarios (temporal, identification, existential) already formed in the mind. The mentioned scenarios are also manifested during free and directed by pair association in the experimental setting.

Gene-Based Association Tests Using GWAS Summary Statistics and Incorporating eQTL

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by the genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose two powerful and computationally efficient gene-based association tests, Overall and Copula. These two tests aggregate information from three traditional types of gene-based association tests and also incorporate expression quantitative trait locus (eQTL) data into GWAS using GWAS summary statistics. Overall utilizes the extended Simes procedure and Copula utilizes the Gaussian copula approximation-based method. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the P values of these two methods can be calculated analytically. Simulation studies show that these two tests can control type I error rate very well and have higher power than the tests that we compared. We also apply these two methods to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that these two newly developed methods can identify more significant genes than other methods we compared with.

Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes

Type 1 diabetes is an autoimmune disease with rising incidence in high-income countries. Genetic and environmental predisposing factors contribute to the etiology of the disease, although their interaction is not sufficiently understood to allow for preventive action. Strongest known associations with genetic variation map to classical HLA class II genes. Because of its genetic complexity, the HLA region has been under-represented in genome-wide association studies, having potentially hindered the identification of relevant associations underlying the etiology of the disease. Here, we performed a comprehensive HLA-wide genetic association analysis of type 1 diabetes including multi-allelic and rare variants. We used high-density whole-exome sequencing data of the HLA region in the large UK Biobank dataset to apply gene-based association tests with a carefully defined type 1 diabetes phenotype (97 cases and 48,700 controls). Exon-based and single-variant association tests were used to complement the analysis. We replicated the known association of type 1 diabetes with the classical HLA-DQ gene. Tailoring the analysis toward rare variants, we additionally identified the lysine methyl transferase EHMT2 as associated. Deeper insight into genetic variation associated with disease as presented and discussed in detail here can help unraveling mechanistic details of the etiology of type 1 diabetes. More specifically, we hypothesize that genetic variation in EHMT2 could impact autoimmunity in type 1 diabetes development.

The temperature of emotions

Emotions and temperature are closely related through embodied processes, and people seem to associate temperature concepts with emotions. While this relationship is often evidenced by everyday language (e.g., cold and warm feelings), what remains missing to date is a systematic study that holistically analyzes how and why people associate specific temperatures with emotions. The present research aimed to investigate the associations between temperature concepts and emotion adjectives on both explicit and implicit levels. In Experiment 1, we evaluated explicit associations between twelve pairs of emotion adjectives derived from the circumplex model of affect, and five different temperature concepts ranging from 0°C to 40°C, based on responses from 403 native speakers of four different languages (English, Spanish, Japanese, Chinese). The results of Experiment 1 revealed that, across languages, the temperatures were associated with different regions of the circumplex model. The 0°C and 10°C were associated with negative-valanced, low-arousal emotions, while 20°C was associated with positive-valanced, low-to-medium-arousal emotions. Moreover, 30°C was associated with positive-valanced, high-arousal emotions; and 40°C was associated with high-arousal and either positive- or negative-valanced emotions. In Experiment 2 (N = 102), we explored whether these temperature-emotion associations were also present at the implicit level, by conducting Implicit Association Tests (IATs) with temperature words (cold and hot) and opposing pairs of emotional adjectives for each dimension of valence (Unhappy/Dissatisfied vs. Happy/Satisfied) and arousal (Passive/Quiet vs. Active/Alert) on native English speakers. The results of Experiment 2 revealed that participants held implicit associations between the word hot and positive-valanced and high-arousal emotions. Additionally, the word cold was associated with negative-valanced and low-arousal emotions. These findings provide evidence for the existence of temperature-emotion associations at both explicit and implicit levels across languages.