A behavioural model of minority language shift: Theory and empirical evidence.
Ontology highlight
ABSTRACT:
SUBMITTER: Uriarte JR
PROVIDER: S-EPMC8177434 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:[This corrects the article DOI: 10.1371/journal.pone.0252453.].
| S-EPMC8270155 | biostudies-literature
Project description:Although understanding the role of the environment is central to language acquisition theory, rarely has this been studied for children's phonetic development, and receptive and expressive language experiences in the environment are not distinguished. This last distinction may be crucial for child speech production in particular, because production requires coordination of low-level speech-motor planning with high-level linguistic knowledge. In this study, the role of the environment is evaluated in a novel way-by studying phonetic development in a bilingual community undergoing rapid language shift. This sociolinguistic context provides a naturalistic gradient of the amount of children's exposure to two languages and the ratio of expressive to receptive experiences. A large-scale child language corpus encompassing over 500 hours of naturalistic South Bolivian Quechua and Spanish speech was efficiently annotated for children's and their caregivers' bilingual language use. These estimates were correlated with children's patterns in a series of speech production tasks. The role of the environment varied by outcome: children's expressive language experience best predicted their performance on a coarticulation-morphology measure, while their receptive experience predicted performance on a lower-level measure of vowel variability. Overall these bilingual exposure effects suggest a pathway for children's role in language change whereby language shift can result in different learning outcomes within a single speech community. Appropriate ways to model language exposure in development are discussed.
| S-EPMC10079255 | biostudies-literature
Project description:Genetic admixture and language shift in the medieval Volga-Oka interfluve
| PRJEB57974 | ENA
Project description:Online communities, which have become an integral part of the day-to-day life of people and organizations, exhibit much diversity in both size and activity level; some communities grow to a massive scale and thrive, whereas others remain small, and even wither. In spite of the important role of these proliferating communities, there is limited empirical evidence that identifies the dominant factors underlying their dynamics. Using data collected from seven large online platforms, we observe a relationship between online community size and its activity which generally repeats itself across platforms: First, in most platforms, three distinct activity regimes exist-one of low-activity and two of high-activity. Further, we find a sharp activity phase transition at a critical community size that marks the shift between the first and the second regime in six out of the seven online platforms. Essentially, we argue that it is around this critical size that sustainable interactive communities emerge. The third activity regime occurs above a higher characteristic size in which community activity reaches and remains at a constant and higher level. We find that there is variance in the steepness of the slope of the second regime, that leads to the third regime of saturation, but that the third regime is exhibited in six of the seven online platforms. We propose that the sharp activity phase transition and the regime structure stem from the branching property of online interactions.
| S-EPMC6333374 | biostudies-literature
Project description:Lexical and morphological knowledge of school-aged children are correlated with each other, and are often difficult to distinguish. One reason for this might be that many tasks currently used to assess morphological knowledge require children to inflect or derive real words in the language, thus recruiting their vocabulary knowledge. The current study investigated the possible separability of lexical and morphological knowledge using two complementary approaches. First, we examined the correlations between vocabulary and four morphological tasks tapping different aspects of morphological processing and awareness, and using either real-word or pseudo-word stimuli. Thus, we tested the hypothesis that different morphological tasks recruit lexical knowledge to various degrees. Second, we compared the Hebrew vocabulary and morphological knowledge of 5th grade language minority speaking children to that of their native speaking peers. This comparison allows us to ask whether reduced exposure to the societal language might differentially influence vocabulary and morphological knowledge. The results demonstrate that indeed different morphological tasks rely on lexical knowledge to varying degrees. In addition, language minority students had significantly lower performance in vocabulary and in morphological tasks that recruited vocabulary knowledge to a greater extent. In contrast, both groups performed similarly in abstract morphological tasks with a lower vocabulary load. These results demonstrate that lexical and morphological knowledge may rely on partially separable learning mechanisms, and highlight the importance of distinguishing between these two linguistic components.
| S-EPMC5826353 | biostudies-literature
Project description:BackgroundDigital education tools (e-learning, technology-enhanced learning) can be defined as any educational intervention that is electronically mediated. Decveloping and applying such tools and interventions for postgraduate medical professionals who work and learn after graduation can be called postgraduate medical digital education (PGMDE), which is increasingly being used and evaluated. However, evaluation has focused mainly on reaching the learning goals and little on the design. Design models for digital education (instructional design models) help educators create a digital education curriculum, but none have been aimed at PGMDE. Studies show the need for efficient, motivating, useful, and satisfactory digital education.ObjectiveOur objective was (1) to create an empirical instructional design model for PGMDE founded in evidence and theory, with postgraduate medical professionals who work and learn after graduation as the target audience, and (2) to compare our model with existing models used to evaluate and create PGMDE.MethodsPreviously we performed an integrative literature review, focus group discussions, and a Delphi procedure to determine which building blocks for such a model would be relevant according to experts and users. This resulted in 37 relevant items. We then used those 37 items and arranged them into chronological steps. After we created the initial 9-step plan, we compared these steps with other models reported in the literature.ResultsThe final 9 steps were (1) describe who, why, what, (2) select educational strategies, (3) translate to the real world, (4) choose the technology, (5) complete the team, (6) plan the budget, (7) plan the timing and timeline, (8) implement the project, and (9) evaluate continuously. On comparing this 9-step model with other models, we found that no other was as complete, nor were any of the other models aimed at PGMDE.ConclusionsOur 9-step model is the first, to our knowledge, to be based on evidence and theory building blocks aimed at PGMDE. We have described a complete set of evidence-based steps, expanding a 3-domain model (motivate, learn, and apply) to an instructional design model that can help every educator in creating efficient, motivating, useful, and satisfactory PGMDE. Although certain steps are more robust and have a deeper theoretical background in current research (such as education), others (such as budget) have been barely touched upon and should be investigated more thoroughly in order that proper guidelines may also be provided for them.
| S-EPMC6876560 | biostudies-literature
Project description:Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.
| S-EPMC9653408 | biostudies-literature
Project description:I study the co-evolution between public opinion and party policy in situations of crises by investigating a policy U-turn of a major Austrian right-wing party (FPÖ) during the Covid-19 pandemic. My analysis suggests the existence of both i) a “Downsian” effect, which causes voters to adapt their party preferences based on policy congruence and ii) a “party identification” effect, which causes partisans to realign their policy preferences based on “their” party's platform. Specifically, I use individual-level panel data to show that i) “corona skeptical” voters who did not vote for the FPÖ in the pre-Covid-19 elections of 2019 were more likely to vote for the party after it embraced “corona populism”, and ii) beliefs of respondents who declared that they voted for the FPÖ in 2019 diverged from the rest of the population in three out of four health-related dimensions only after the turn, causing them to underestimate the threat posed by Covid-19 compared to the rest of the population. Using aggregate-level panel data, I study whether the turn has produced significant behavioral differences which could be observed in terms of reported cases and deaths per capita. Paradoxically, after the turn the FPÖ vote share is significantly positively correlated with deaths per capita, but not with the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing, which causes a correlation between the number of “corona skeptics” and the share of unreported cases after the turn. I find empirical support for this hypothesis in individual-level data from a Covid-19 prevalence study that involves information about participants’ true vs. reported infection status. I finally study a simple heterogeneous mixing epidemiological model and show that a testing bias can indeed explain the apparent paradox of an increase in deaths without an increase in reported cases. My results can, among others, be used to enrich formal analyses regarding the co-evolution between voter and party behavior.
| S-EPMC10017277 | biostudies-literature
Project description:Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.
| S-EPMC4570551 | biostudies-literature
Project description:Using the bifactor item response theory model to analyze data arising from educational and psychological studies has gained popularity over the years. Unfortunately, using this model in practice comes with challenges. One such challenge is an empirical identification issue that is seldom discussed in the literature, and its impact on the estimates of the bifactor model's parameters has not been demonstrated. This issue occurs when an item's discriminations on the general and specific dimensions are approximately equal (i.e., the within-item discriminations are similar in strength), leading to difficulties in obtaining unique estimates for those discriminations. We conducted three simulation studies to demonstrate that within-item discriminations being similar in strength creates problems in estimation stability. The results suggest that a large sample could alleviate but not resolve the problems, at least when considering sample sizes up to 4,000. When the discriminations within items were made clearly different, the estimates of these discriminations were more consistent across the data replicates than that observed when the discriminations within the items were similar. The results also show that the similarity of an item's discriminatory magnitudes on different dimensions has direct implications on the sample size needed in order to consistently obtain accurate parameter estimates. Although our goal was to provide evidence of the empirical identification issue, the study further reveals that the extent of similarity of within-item discriminations, the magnitude of discriminations, and how well the items are targeted to the respondents also play factors in the estimation of the bifactor model's parameters.
| S-EPMC9574084 | biostudies-literature