What are Funds of Knowledge? A Collaborative Approach to Education

It is important as educators to have a holistic understanding of students’ identities as these experiences influence classroom dynamics. As noted by Dugan (2017), “…identity, knowledge, and power are influenced profoundly by ideology and hegemony and in turn play a role in shaping people’s stocks of knowledge” (p. 40). “Stocks of knowledge” are characterized by five principles: they are familiar, serve to help navigate the world, “shaped by lived experience, altered only through novel situations, and socially constructed based on identity” (Dugan, 2017, p. 34). These “stocks of knowledge” are also known as “funds of knowledge” by multicultural educators.https://digitalscholarship.unlv.edu/btp_expo/1052/thumbnail.jp

Understanding the Professional Experiences of White Jewish Women in Higher Education: An Intrinsic Case Study Analysis

The exploration of female professionals’ experiences within the realm of higher education is steadily increasing, yet researchers have yet to analyze, much less include, Jewish women. Following a qualitative intrinsic case study approach, this study assesses the lived experiences of ten white Jewish women professionals to better understand how they engage in the world of higher education differently than their non-Jewish counterparts. Using racial formation theory and intersectional analysis as theoretical frameworks, the research examined the current and historical literature on Jewish identity, the role of Jews and Jewish women in higher education, and the relevant methodological research. The study discovered that Jewish women higher education professionals (a) identify racially white based on the current socio-political landscape; (b) the participant’s intersectional identities impact their professional identity; (c) four strategies were identified by the professionals to navigate academia. Additionally, the research provides recommendations to better support Jewish women professionals in the field, thus helping to inform institutional policies and practices in postsecondary education. As a result, this examination fills a much-needed gap in the literature providing a basis of knowledge for future scholars to explore this phenomenon

Structural Brain Correlates of Childhood Inhibited Temperament: An ENIGMA-Anxiety Mega-analysis

Temperament involves stable behavioral and emotional tendencies that differ between individuals, which can be first observed in infancy or early childhood and relate to behavior in many contexts and over many years.1 One of the most rigorously characterized temperament classifications relates to the tendency of individuals to avoid the unfamiliar and to withdraw from unfamiliar people, objects, and unexpected events. This temperament is referred to as behavioral inhibition or inhibited temperament (IT).2 IT is a moderately heritable trait1 that can be measured in multiple species.3 In humans, levels of IT can be quantified from the first year of life through direct behavioral observations or reports by caregivers or teachers. Similar approaches as well as self-report questionnaires on current and/or retrospective levels of IT1 can be used later in life

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size, and have limited clinical relevance. These concerns have prompted a paradigm shift towards highly powered (i.e., big data) individual-level inferences, which are data-driven, transdiagnostic, and neurobiologically informed. Hence, we uniquely built/validated supervised neuroanatomical machine learning (ML) models for individual-level inferences, using the largest up to date neuroimaging database on youth anxiety disorders: ENIGMA Anxiety Consortium (N=3,343; Age: 10-25 years; Global Sites: 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (Panic Disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status, and symptom severity (AUC’s 0.59-0.63). Classifications were driven by neuroanatomical features (cortical thickness/surface area, subcortical volumes) in fronto-striato-limbic and temporo-parietal regions. This benchmark study provides estimates on individual-level classification performances that can be realistically achieved with ML using neuroanatomical data, within a large, heterogenous, and multi-site sample of youth with anxiety disorders

Structural brain correlates of childhood inhibited temperament: An ENIGMA-anxiety mega-analysis

NWORubicon 019.201SG.022Pathways through Adolescenc