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Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is necessary to consider the most appropriate ways to analyze this data to draw causal inferences from RCTs. Here, we examine whether and how analysis results are impacted by accounting for multilevel variance in samples from RCTs with student-level randomization within one platform. We propose and demonstrate a method that leverages auxiliary non-experimental "remnant" data collected within a learning platform to inform analysis decisions. Specifically, we compare five commonly-applied analysis methods to estimate treatment effects while accounting for, or ignoring, class-level factors and observed measures of confidence and accuracy to identify best practices under real-world conditions. We find that methods that account for groups as either fixed effects or random effects consistently outperform those that ignore group-level factors, even though randomization was applied at the student level. However, we found no meaningful differences between the use of fixed or random effects as a means to account for groups. We conclude that analyses of online experiments should account for the naturally-nested structure of students within classes, despite the notion that student-level randomization may alleviate group-level differences. Further, we demonstrate how to use remnant data to identify appropriate methods for analyzing experiments. These findings provide practical guidelines for researchers conducting RCTs in similar educational technologies to make more informed decisions when approaching analyses. [ABSTRACT FROM AUTHOR]

The study aimed to determine the sociodemographic and psychological profiles of drivers with a history of motor vehicle crashes (MVCs), following the contextual-mediated model of crash involvement, and trying to define similarities and differences with drivers without MVCs. Although road trauma prevention has become a central public health issue, the study of psychological determinants of MVCs does not have consistent results due to methodological and theoretical weaknesses. Three-hundred and forty-five active drivers (20% females) completed an extensive office-based fitness-to-drive evaluation including measures of cognition, personality, self-reported driving-related behaviors, attitudes, as well as computerized measures of driving performance. The Classification and Regression Tree method (CART) was used to identify discriminant predictors. The classification identified several relevant predictors; the personality trait of Discostraint (as a distal context variable; cut-point: 50 T points) and motor speed (as a proximal context variable; cut-point: 64 percentile ranks). The global classification model increased approximately 3 times the probability of identifying people with a history of MVC involvement, starting from an estimated prevalence of being involved in an MVC in a period of five years in the population of active drivers. Consistent with the 'contextual-mediated model of traffic accident involvement', the results of the present study suggest that road trauma analysis should focus on both distal and proximal driver-related factors by paying attention to their association in determining MVCs. These results represent a valuable source of knowledge for researchers and practitioners for preventing road trauma. [ABSTRACT FROM AUTHOR]

The human gut microbiota refers to a diverse community of microorganisms that symbiotically exist in the human intestinal system. Altered microbial communities have been linked to many human pathologies. However, there is a lack of rapid and efficient methods to assess gut microbiota signatures in practice. To address this, we established an appraisal system containing 45 quantitative real-time polymerase chain reaction (qPCR) assays targeting gut core microbes with high prevalence and/or abundance in the population. Through comparative genomic analysis, we selected novel species-specific genetic markers and primers for 31 of the 45 core microbes with no previously reported specific primers or whose primers needed improvement in specificity. We comprehensively evaluated the performance of the qPCR assays and demonstrated that they showed good sensitivity, selectivity, and quantitative linearity for each target. The limit of detection ranged from 0.1 to 1.0 pg/µL for the genomic DNA of these targets. We also demonstrated the high consistency (Pearson's r = 0.8688, P < 0.0001) between the qPCR method and metagenomics next-generation sequencing (mNGS) method in analyzing the abundance of selected bacteria in 22 human fecal samples. Moreover, we quantified the dynamic changes (over 8 weeks) of these core microbes in 14 individuals using qPCR, and considerable stability was demonstrated in most participants, albeit with significant individual differences. Overall, this study enables the simple and rapid quantification of 45 core microbes in the human gut, providing a promising tool to understand the role of gut core microbiota in human health and disease. Key points: • A panel of original qPCR assays was developed to quantify human gut core microbes. • The qPCR assays were evaluated and compared with mNGS using real fecal samples. • This method was used to dynamically profile the gut core microbiota in individuals. [ABSTRACT FROM AUTHOR]

There is an expectation that health professions schools respond to priority societal health needs. This expectation is largely based on the underlying assumption that schools are aware of the priority needs in their communities. This paper demonstrates how open-access, pan-national health data can be used to create a reliable health index to assist schools in identifying societal needs and advance social accountability in health professions education. Using open-access data, a psychometric evaluation was conducted to examine the reliability and validity of the Canadian Health Indicators Framework (CHIF) conceptual model. A non-linear confirmatory factor analysis (CFA) on 67 health indicators, at the health-region level (n = 97) was used to assess the model fit of the hypothesized 10-factor model. Reliability analysis using McDonald's Omega were conducted, followed by Pearson's correlation coefficients. Findings from the non-linear CFA rejected the original conceptual model structure of the CHIF. Exploratory post hoc analyses were conducted using modification indices and parameter constraints to improve model fit. A final 5-factor multidimensional model demonstrated superior fit, reducing the number of indicators from 67 to 32. The 5-factors included: Health Conditions (8-indicators); Health Functions (6-indicators); Deaths (5-indicators); Non-Medical Health Determinants (7-indicators); and Community & Health System Characteristics (6-indicators). All factor loadings were statistically significant (p < 0.001) and demonstrated excellent internal consistency (ω >0.95). Many schools struggle to identify and measure socially accountable outcomes. The process highlighted in this paper and the indices developed serve as starting points to allow schools to leverage open-access data as an initial step in identifying societal needs. [ABSTRACT FROM AUTHOR]

One of the most fundamental problems many students face in school is bullying. This form of harassment, known as cyberbullying, has emerged as the use of the internet and other digital media has increased in recent years. The purpose of this study is to determine the extent of secondary school students' cyberbullying and cyber victimization experiences, to see if there is a correlation between cyberbullying and cyber victimization, and to explore how students' cyberbullying or cyber victim status influences their cyber victim or cyberbullying behavior. Unlike experimental studies, which use manipulation and random assignment of participants and conditions, the study employed a causal-comparative research design, in which the researcher investigates the causes and consequences of differences between groups. The sample group of the study consists of 286 secondary school students in the fifth, sixth, and seventh grades who were recruited using the typical case sampling method, which is one of the purposive sampling methods. The data were collected via the scales of cyberbullying and cyber victimization. According to the findings, cyberbullying is significantly and positively influenced by cyber victimization. Instead of looking at cyberbullying in isolation, it was suggested that a more effective approach to solving the problem would be to integrate cyberbullying and cyber victimization holistically. [ABSTRACT FROM AUTHOR]

Objectives: Scholars and practitioners have paid increasing attention to problematic properties, but little is known about how they emerge and evolve. We examine four phenomena suggested by life-course theory that reflect stability and change in crime and disorder at properties: onset of issues; persistence of issues; aggravation to more serious types of issues; and desistance of issues. We sought to identify the frequency and dynamics of each. Methods: We analyze how residential parcels (similar to properties) in Boston, MA shifted between profiles of crime and disorder from 2011 to 2018. 911 dispatches and 311 requests provided six measures of physical disorder, social disorder, and violence for all parcels. K-means clustering placed each parcel into one of six profiles of crime and disorder for each year. Markov chains quantified how properties moved between profiles year-to-year. Results: Onset was relatively infrequent and more often manifested as disorder than violence. Pathways of aggravation led from less serious profiles to a mixture of violence and disorder. Desistance was more likely to occur as de-escalations along these pathways then complete cessation of issues. In neighborhoods with above-average crime, persistence was more prevalent whereas desistance less often culminated in cessation, even relative to local expectations. Conclusions: The results offer insights for further research and practice attentive to trends of crime and disorder at problematic properties. It especially speaks to the understanding of stability and change; the role of different types of disorder; and the toolkit needed for problem properties interventions. [ABSTRACT FROM AUTHOR]

Rapid climate and socioeconomic changes are transforming Arctic human–earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. In addition, underrepresented were methods explicitly considering adaptive capacity of transportation systems. We provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems, laying a foundation for future work that investigates how these impacts fit into broader human–arth systems. [ABSTRACT FROM AUTHOR]

Using five years of publishing data from the Journal of Higher Education, we describe the publication pipeline at the journal, explore trends with respect to topic, the geographic distribution of authors, and each paper's methodological approach. Following the presentation of these trends, we discuss implications for the field of higher education and those publishing within it. [ABSTRACT FROM AUTHOR]

With the growth of third sector research, the field needs more dedicated discussion on how we study the third sector, not only the decisions in research design or data collection process but also the general research approaches and the way we analyze the data. In this introduction to the special issue of Voluntas Volume I, we discuss how the sector can foster a more inclusive and diverse research community for people, topics, and methods. We also discuss the implications of methodological pluralism, an organizing principle of a research community that fosters respect, appreciation, and empathy between its members. We conclude by calling for more empathetic, transparent, and accountable research. [ABSTRACT FROM AUTHOR]

The Industry 4.0 (I4.0) concept paves the way for the circular economy (CE) as advanced digital technologies enable sustainability initiatives. Hence, I4.0-driven CE-oriented supply chains (SCs) have improved sustainable performance, flexibility and interoperability. In order to smoothly embrace circular practices in digitally enabled SCs, quantitative techniques have been identified as crucial. Therefore, the intersection of I4.0, CE, supply chain management (SCM) and quantitative techniques is an emerging research arena worthy of investigation. This article presents a bibliometric analysis to identify the established and evolving research clusters in the topological analysis by identifying collaboration patterns, interrelations and the studies that significantly dominate the intersection of the analysed fields. Further, this study investigates the current research trends and presents potential directions for future research. The bibliometric analysis highlights that additive manufacturing (AM), big data analytics (BDA) and the Internet of Things (IoT) are the most researched technologies within the intersection of CE and sustainable SCM. Evaluation of intellectual, conceptual and social structures revealed that I4.0-driven sustainable operations and manufacturing are emerging research fields. This study provides research directions to guide scholars in the further investigation of these four identified fields while exploring the potential quantitative methods and techniques that can be applied in I4.0-enabled SCs in the CE context. [ABSTRACT FROM AUTHOR]

Scholars have offered a range of perspectives on the twenty-first century racial landscape with little consensus about either the current state of the U.S. racial hierarchy or its future trajectory. We offer a more comprehensive assessment, using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to study racial stratification across a number of socioeconomic outcomes. We pay particular attention to the robustness of results across different categorization schemes that account for self-identification and interviewer classification, as well as racial fluidity. Although we observe that White and Asian Americans generally have the best socioeconomic outcomes, on average, while Black Americans and American Indians have the worst, we also find meaningful differences in patterns of stratification both across outcomes and depending on how race is operationalized. These differences in stratification are reflected in the estimated number of strata as well as the rank order of racial categories. Our results suggest that ongoing debates about the nature of the U.S. racial hierarchy can be partly explained by methodological decisions about which outcomes to study and how best to measure race. [ABSTRACT FROM AUTHOR]

Certain places generate inordinate amounts of crime and disorder. We examine how places differ in their nature of crime and disorder, with three objectives: (1) identifying a typology of profiles of crime and disorder; (2) assessing whether different forms of crime and disorder co-locate at parcels; and (3) determining whether problematic parcels explain crime and disorder across neighborhoods. The study uses 911 and 311 records to quantify physical and social disorder and violent crime at residential parcels in Boston, MA (n = 81,673). K-means cluster analyses identified the typology of problematic parcels and how those types were distributed across census block groups. Cluster analysis identified five types of problematic parcels, four specializing in one form of crime or disorder and one that combined all issues. The second cluster analysis found that the distribution of problematic parcels described the spectrum from low- to high-crime neighborhoods, plus commercial districts with many parcels with public physical disorder. Problematic parcels modestly explained levels of crime across neighborhoods. The results suggest a need for diverse intervention strategies to support different types of problematic parcels; and that neighborhood dynamics pertaining to crime are greater than problematic properties alone. [ABSTRACT FROM AUTHOR]

Objectives: Much recent work has focused on how crime concentrates on particular streets within communities. This is the first study to examine how such concentrations vary across the neighborhoods of a city. The analysis evaluates the extent to which neighborhoods have characteristic levels of crime concentration and then tests two hypotheses for explaining these variations: the compositional hypothesis, which posits that neighborhoods whose streets vary in land usage or demographics have corresponding disparities in levels of crime; and the social control hypothesis, which posits that neighborhoods with higher levels of collective efficacy limit crime to fewer streets. Methods: We used 911 dispatches from Boston, MA, to map violent crimes across the streets of the city. For each census tract we calculated the concentration of crime across the streets therein using the generalized Gini coefficient and cross-time stability in the locations of hotspots. Results: Neighborhoods did have characteristic levels of concentration that were best explained by the compositional hypothesis in the form of demographic and land use diversity. In addition, ethnic heterogeneity predicted higher concentrations of crime over and above what would be expected given the characteristics of the individual streets, suggesting it exacerbated disparities in crime. Conclusions: The extent to which crime concentrates represents an underexamined aspect of how crime manifests in each community. It is driven in part by the diversity of places in the neighborhood, but also can be influenced by neighborhood-level processes. Future work should continue to probe the sources and consequences of these variations. [ABSTRACT FROM AUTHOR]

Copyright of Politische Vierteljahresschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Parents' intentions to engage in parent-child sexual communication (PCSC) are largely understudied, especially when children are young. Based on the theory of planned behavior (TPB), this study aimed to explore what factors are associated with parental intentions to talk with their children about different sexual topics. Method: A sample of 561 parents of an oldest child between the ages of 6 and 11 were recruited to complete a survey through Prolific.co between December 2019 and January 2020. Results: Results of a path analysis showed that all components of the TPB (attitudes, subjective norms, self-efficacy) were significantly associated with parents' intentions to talk to their children about at least three of the five categories of sexual topics ("the basics," "pleasure," "sex in relationships," "gender identity/sexual orientation," and the "religious meaning of sex"). Of these components, self-efficacy was most consistently and strongly associated with increased intentions to discuss all topics, followed by the attitude of believing sex education was the parents' responsibility. Conclusion: These findings support the assumptions of the TPB as applied to PCSC. These findings suggest that building self-efficacy and helping parents feel responsible for educating their children about sex would be most important in attempting to increase parental intentions to engage in PCSC on a wide variety of topics. Policy Implications: Funding for parent-targeted programming should be allocated to increase parent intentions to engage in PCSC. This programming should focus on helping parents develop self-efficacy and a sense of responsibility for educating children about multiple sexual topics. [ABSTRACT FROM AUTHOR]

This study examines the way in which student characteristics and pre-admissions measures are statistically associated with the likelihood a student will require remediation for academic and professionalism offenses. We anchor our inquiry within Irby and Hamstra's (2016) conceptual framework of constructs of professionalism. Data from five graduating cohorts (2014–2018) from McMaster University (Hamilton, Canada) (N = 1,021) were retroactively collected and analyzed using traditional and multinominal logistic regression analyses. The relationship among student characteristics, pre-admissions variables, and referral for potential remediation both by occurrence (yes/no) as well as type (academic/professional/no referral) were examined separately. Findings indicate that gender (OR = 0.519, 95% CI 0.326–0.827, p < 0.01) and undergraduate grade point average (GPA) (OR = 0.245, 95% CI 0.070–0.855, p < 0.05) were significantly associated with instances of referral for potential professionalism and academic remediation, respectively. Women were less likely than men to require remediation for professionalism (OR = 0.332, 95% CI 0.174–0.602, p < 0.001). Undergraduate GPAs (OR = 0.826, 95% CI 0.021–0.539, p < 0.01) were significantly associated with remediation for academic reasons. Lower undergraduate GPAs were associated with a higher likelihood of remediation. These findings point to the admissions variables that are associated with instances that prompt referral for potential remediation. Where associations are not significant, we consider the application of different conceptualizations of professionalism across periods of admissions and training. We encourage those involved in applicant selection and student remediation to emphasize the importance of the interactions that occur between personal and contextual factors to influence learner behaviour and professional identity formation. [ABSTRACT FROM AUTHOR]

The construction industry has been greatly developed in the past few decades, especially in the extensive use of underground space. The increasing amount of waste (e.g., soil, sludge, and rock) generated in the underground construction constitutes an important part of construction and demolition waste (CDW), but the related problems are rarely addressed in an independent quantitative study. In order to facilitate recycling of underground construction waste (UCW), quantitative methods for predicting UCW are proposed based on mass conservation in this study. Through on-site investigation and literature review, the source characteristics of UCW and corresponding recycling potential are firstly analyzed. Secondly, the corresponding quantitative method is proposed for predicting each type of UCW according to the principle of mass conservation. Finally, the proposed quantitative methods are applied in two real underground infrastructure projects to verify the accuracy. The results show that the accuracy of quantitative methods for predicting shield sludge and engineering soil is 82.03–95.79% and 94.49% respectively. The quantitative methods for predicting the amount of UCW proposed in this study is effective. In both cases, underground construction produced a large amount of construction waste with great recycling potential. UCW can theoretically reach 100% recycling, and full reuse and recycling of UCW will bring huge benefits and be conducive to the sustainable development of the construction industry. [ABSTRACT FROM AUTHOR]

Rainfall-induced landslides are an important type of dangerous natural disaster worldwide and have always been the focus of research. Yet, the impact of seasonal rainfall on landslides at the landscape scale is still poorly understood due to a paucity of effective observation data and appropriate quantitative methods. Therefore, with the support of Interferometic Synthetic Aperture Radar (InSAR) technique, in this study, the time series displacement datum of landslides was accurately recorded, and combined with the time–frequency analysis method, wavelet analysis, the influence of rainfall on the deformation of the landslide in the study area was quantitatively studied. The results suggest that the satellite radar images can effectively record the landslide deformation data and provide data support for further research, whose combination with wavelet analysis has novelty and applicability in the study of rainfall-induced landslides. Both rainfall and landslide deformation have periods of about 1 year on the inter-annual scale, and they also exhibit obvious seasonal variations on the annual scale. There is a strong positive correlation between the two and a lag time of about 45 days. These results provide a basis for the quantitative study of the relationship between rainfall and landslide displacement, which is crucial to effective and reasonable disaster prevention and control. [ABSTRACT FROM AUTHOR]

Algal biomass has been utilized as a potential feedstock for bioenergy and a variety of other bioprocesses. At the core of this topic, there is a general demand for rapid, cost-effective, and accurate methods for algal biomass quantification. Here, we present a simple, low-cost, and non-destructive method to estimate algal biomass concentrations by image analysis based on the hue, saturation, intensity (HSI) color space. The applicability of the HSI-based quantitative method was verified using experimental data from both the present study and the literature. In addition, the HSI-based quantitative method showed better goodness of fit and a significantly higher detection range than related methods used in the literature. The results indicate that the HSI-based quantitative method can be used as an effective method for algal biomass monitoring and quantification. [ABSTRACT FROM AUTHOR]

A quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance. [ABSTRACT FROM AUTHOR]

Using quantitative methods, we investigate the role of logic in analytic philosophy from 1941 to 2010. In particular, a corpus of five journals publishing analytic philosophy is assessed and evaluated against three main criteria: the presence of logic, its role and level of technical sophistication. The analysis reveals that (1) logic is not present at all in nearly three-quarters of the corpus, (2) the instrumental role of logic prevails over the non-instrumental ones, and (3) the level of technical sophistication increases in time, although it remains relatively low. These results are used to challenge the view, widespread among analytic philosophers and labeled here "prevailing view", that logic is a widely used and highly sophisticated method to analyze philosophical problems. [ABSTRACT FROM AUTHOR]

Archaeologists employ an array of comparative approaches to assess zooarchaeological assemblages and the human behavior that produced them. Similarity indices are a simple and effective method for evaluating correspondence between the taxa present and their abundances in two zooarchaeological assemblages. Yet, these indices are not as widely used as other approaches. Here, I review several similarity metrics and present a method for measuring assemblage similarity using paired incidence- and abundance-based indices. The combined results of these measures can be used to classify a set of assemblages according to their dissimilarity, qualitative similarity, quantitative similarity, or substantive similarity. The paired-index approach is demonstrated employing the corrected Forbes and Morista-Horn indices in two zooarchaeological case studies from the Caribbean sites of Sabazan (Carriacou), Sandy Ground (Anguilla), and Crève Coeur (Martinique) in the Lesser Antilles. I show that the method (1) provides a means to quantify the similarity between assemblages along a defined, meaningful scale; (2) offers a straightforward approach for understanding how the dimensions of assemblage similarity interact based on a proposed classification scheme; and (3) constitutes a simple-to-apply technique requiring minimal technical skills. I conclude by discussing the strengths and limitations of this method and its potential wider application in archaeology. [ABSTRACT FROM AUTHOR]

It is a well-known practice in software engineering to aggregate software metrics to assess software artifacts for various purposes, such as their maintainability or their proneness to contain bugs. For different purposes, different metrics might be relevant. However, weighting these software metrics according to their contribution to the respective purpose is a challenging task. Manual approaches based on experts do not scale with the number of metrics. Also, experts get confused if the metrics are not independent, which is rarely the case. Automated approaches based on supervised learning require reliable and generalizable training data, a ground truth, which is rarely available. We propose an automated approach to weighted metrics aggregation that is based on unsupervised learning. It sets metrics scores and their weights based on probability theory and aggregates them. To evaluate the effectiveness, we conducted two empirical studies on defect prediction, one on ca. 200 000 code changes, and another ca. 5 000 software classes. The results show that our approach can be used as an agnostic unsupervised predictor in the absence of a ground truth. [ABSTRACT FROM AUTHOR]

Much attention has been paid to the effects of the COVID-19 pandemic on long-term care but the impact on informal caregivers has remained speculative. In Austria, like in other European countries, informal care is carried out overwhelmingly by (non-cohabiting) relatives. Limited care services available during the pandemic, social-distancing, increased unemployment and competing care needs within households (e.g. due to school closures) may have changed the prevalence and intensity of informal caregiving. Moreover, these changes may have increased the psychological strain experienced by caregivers. Focusing on Austria, this study aims to empirically analyse the following research questions: how have the prevalence and intensity of informal care changed due to the pandemic? How has the psychological well-being of informal caregivers been affected? We use a pre- and post-onset of the pandemic research design based on a representative survey carried out in Austria in June 2020 (N = 2000) in combination with comparable 2015 data from the European Social Survey. Findings suggest that neither prevalence nor intensity of informal care changed significantly due to the pandemic. However, the psychological well-being gap between carers and non-carers increased with the start of the pandemic, especially among men. Findings are discussed in relation to the policy measures implemented and possible policy implications for the future. [ABSTRACT FROM AUTHOR]

Quantitative analysis of modified barium swallow (MBS) imaging is useful to determine the impact of various disease states on pharyngeal swallowing mechanics. In this retrospective proof of concept study, kinematic analysis and computational analysis of swallowing mechanics (CASM) were used to demonstrate how these methods differentiate swallowing dysfunction by dysphagia etiology. Ten subjects were randomly selected from four cohorts of dysphagic patients including COPD, head and neck cancer (HNC), motor neuron disease, and stroke. Each subject was age- and gender-matched with healthy, non-dysphagic controls. MBS videos of 5 ml thin and 5 ml thick bolus trials from each subject were used. A MATLAB tracker tool was adapted and updated to collect and compile data for each video (n = 160). For kinematic measurements, a MANOVA was performed with post-hoc analyses to determine group differences. For CASM measurements, a morphometric canonical variate analysis with post hoc analysis was performed to determine group differences. Kinematic analyses indicated statistically significant differences between HNC cohort and controls in distance measurements for hyolaryngeal approximation (p =.001), laryngeal elevation (p = 0.0001), pharyngeal shortening (p = 0.0002), and stage transition duration timing (p = 0.002). Timing differences were noted between the stroke cohort and controls for pharyngeal transit time (p = 0.007). Multivariate morphometric canonical variate analysis showed significant differences between etiology groups (p < 0.0001) with eigenvectors indicating differing patterns of swallowing mechanics. This study demonstrated that swallowing mechanics among cohorts of dysphagic patients can be differentiated using kinematics and CASM, providing different but complementary quantitative methods for investigating the impact of various disease states on swallowing function. [ABSTRACT FROM AUTHOR]

This study addresses stratification in the global higher education research community and the changing geography of country affiliations in six elite journals. The distribution of country affiliations is analyzed from a longitudinal perspective (1996–2018), and full-time and part-time authors in the field are contrasted. The prestige maximization model and principal-agent theory provide the theoretical framework for the study, which examines 6334 articles published in six elite journals in the context of 21,442 articles in 41 core journals. The findings indicate that about 3.3% of academics have authored at least five articles (full-timers). These authors constitute the publishing core of the research community, while the 80% who have authored one article (part-timers) constitute its periphery. Higher Education (HE) and Studies in Higher Education (SHE) emerge as elite global journals, with an increasing share of non-Anglo-Saxon authors. Previously globally invisible countries became visible almost exclusively through HE and SHE. Global trends include the diminishing role of American researchers and the increasing role of researchers from Continental Europe, East Asia, and the cluster of 66 "other" countries. The single biggest affiliation loser is the United States, which had 42.5% of country affiliations in 1996–2003 but only 26.9% in 2012–2018. This reflects both the increasing share of non-American affiliations and the increasing yearly volume of HE and SHE publications, in which US academics tend not to publish massively. [ABSTRACT FROM AUTHOR]

Copyright of JMD: Journal für Mathematik-Didaktik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Politische Vierteljahresschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There are various statistical methods serving to analyse data and test hypotheses. The structural equation modelling method is nonetheless one of the most widespread as it allows to estimate complex causal relationships between different variables. Moreover, has been greatly promoted since the emergence of new information and communication technologies. This paper presents a quantitative study of the performance and evolution of research applying structural equation modelling in Social Sciences. SciMAT software has served for the bibliometric analysis. The results indicate that the thematic areas revealing the greatest relevance throughout the last three decades (1990–2019) are behaviour and health. This contribution of this study is that it offers a comprehensive view of the status quo and predicts further research trends. [ABSTRACT FROM AUTHOR]

One of the most challenging problems in personnel selection is the multi-attribute nature of the candidates. This problem is magnified during the procedure of selection of sophisticated personnel, such as internal auditors. By definition, an internal auditor must combine a selection of analytical and non-analytical skills, corresponding to specific cognitive and behavioral attributes. In this paper, a framework for internal auditors' selection using TOPSIS technique is proposed, integrating behavioral and cognitive skills. AHP technique has been used to determine the weights of each criterion. By prioritizing the latter skills, the proposed framework can identify employable and potentially employable candidates. Besides considering the desirable skills in the process of personnel selection, the expected performance is also taken into account. To examine what would be the ideal importance of cognitive and behavioral skills that maximizes candidates' performance, a non-linear programming method is applied. A real-life application is demonstrated to a sample of internal auditors from the Greek branch of a multi-national company. [ABSTRACT FROM AUTHOR]

Research suggests that a sense of belonging is a critical prerequisite of happiness and well-being. While some have focused on belonging provided by relationships, other work demonstrates the value of belonging in certain places. In the current research we join these efforts to understand belonging by offering a novel framework for exploring an understudied but no less fundamental aspect of human experience—time. We situate this framework within an existential analysis of human action and test general predictions about the psychological value of experiencing a sense of belonging in time, what we call temporal rootedness. Two samples (Studies 1 and 2) collected across cultures provide converging evidence that temporal rootedness is a unique psychological phenomenon that is predictive of personal psychological well-being. Two additional experiments (Studies 3 and 4) offer promising evidence that temporal rootedness can be situationally induced and threatened with consequences for well-being. These findings demonstrate the potential value of further exploration into this sense of belonging. [ABSTRACT FROM AUTHOR]

Researchers misunderstand their role in creating ethical problems when they allow dogmas to purportedly divorce scientists and scientific practices from the values that they embody. Cortina (J Bus Ethics. 10.1007/s10551-019-04195-8, 2019), Edwards (J Bus Ethics. 10.1007/s10551-019-04197-6, 2019), and Powell (J Bus Ethics. 10.1007/s10551-019-04196-7, 2019) help us clarify and further develop our position by responding to our critique of, and alternatives to, this misleading separation. In this rebuttal, we explore how the desire to achieve the separation of facts and values is unscientific on the very terms endorsed by its advocates—this separation is refuted by empirical observation. We show that positivists like Cortina and Edwards offer no rigorous theoretical or empirical justifications to substantiate their claims, let alone critique ours. Following Powell, we point to how classical pragmatism understands 'purpose' in scientific pursuits while also providing an alternative to the dogmas of positivism and related philosophical positions. In place of dogmatic, unscientific cries about an abstract and therefore always-unobservable 'reality,' we invite all organizational scholars to join us in shifting the discussion about quantitative research towards empirically grounded scientific inquiry. This makes the ethics of actual people and their practices central to quantitative research, including the thoughts, discourses, and behaviors of researchers who are always in particular places doing particular things. We propose that quantitative researchers can thus start to think about their research practices as a kind of work, rather than having the status of a kind of dogma. We conclude with some implications that this has for future research and education, including the relevance of research and research methods. [ABSTRACT FROM AUTHOR]

The importance of internal audit and its impact on the organizations' effectiveness raised public interest. This study focuses on the internal control mechanisms in the local government organizations (LGO). Specifically, the level of implementation of internal corporate control mechanisms in the Decision Support Department (DSD) of the LGOs is explored. On the basis of data analysis and processing of the results of the study, in which 93 civil servants took part, it is evident that the degree of the added value of internal audit in public organizations depends on the degree of its independency. Also, findings suggest that it is inversely proportional to the degree of compliance with procedures of the DSD. The analysis is extended by incorporating mathematical programming techniques for subset variable selection in order to minimize error values. Decision variables of the proposed models indicate which of the variables will be included in the regression model, to increase adjusted R2. [ABSTRACT FROM AUTHOR]

Throughout history, race and ethnicity have been used as key descriptors to categorize and label individuals. The use of these concepts as variables can impact resources, policy, and perceptions in medical education. Despite the pervasive use of race and ethnicity as quantitative variables, it is unclear whether researchers use them in their proper context. In this Eye Opener, we present the following seven considerations with corresponding recommendations, for using race and ethnicity as variables in medical education research: 1) Ensure race and ethnicity variables are used to address questions directly related to these concepts. 2) Use race and ethnicity to represent social experiences, not biological facts, to explain the phenomenon under study. 3) Allow study participants to define their preferred racial and ethnic identity. 4) Collect complete and accurate race and ethnicity data that maximizes data richness and minimizes opportunities for researchers' assumptions about participants' identity. 5) Follow evidence-based practices to describe and collapse individual-level race and ethnicity data into broader categories. 6) Align statistical analyses with the study's conceptualization and operationalization of race and ethnicity. 7) Provide thorough interpretation of results beyond simple reporting of statistical significance. By following these recommendations, medical education researchers can avoid major pitfalls associated with the use of race and ethnicity and make informed decisions around some of the most challenging race and ethnicity topics in medical education. [ABSTRACT FROM AUTHOR]

Background: There are limited quantitative approaches for evaluating rare safety outcomes from controlled clinical trials in either a blinded or unblinded setting. This manuscript demonstrates an application of three statistical methods for quantitative safety monitoring that can be implemented during any phase of a clinical trial, including open-label extension studies. Methods: An interactive safety monitoring (iSM) tool was developed using R language in the publicly available R-Shiny app and was implemented for three statistical methods of quantitative safety monitoring. These methods are sequential probability ratio test (SPRT), maximized SPRT (MaxSPRT), and Bayesian posterior probability threshold (BPPT). The iSM tool evaluated specific safety signals that incorporated pre-specified background rates or reference risk ratios. Results: Two sets of blinded clinical trial data were used for case studies to demonstrate the use the iSM tool. Two particular adverse events, myocardial infarction (MI) and serious infection, were monitored. Monte Carlo simulation was conducted to evaluate the operating characteristics of pre-specified parameters. It showed that after adjusting for exposure, the BPPT and MaxSPRT yielded similar results in identifying a pre-specified signals while the SPRT method failed to detect such signals. Conclusion: Statistical methods shown for the case studies, as well as the application of the user-friendly iSM tool, greatly enhance the quantitative monitoring of safety events of interest in ongoing clinical trials The BPPT and MaxSPRT methods seem more sensitive in picking-up early signals than the SPRT method when the number of safety events is small. [ABSTRACT FROM AUTHOR]

Many primates show responses to dead infants, yet testing explanations for these behaviors has been difficult. Callitrichids present a unique opportunity to delineate between hypotheses, since unlike most species, male caretakers form closer social bonds with infants than mothers. Callitrichids are also known to commit infanticide, leaving obvious wounds that may enable them to more readily recognize death. We present: (1) a case study of a wild common marmoset (Callithrix jacchus) group responding to an infant's natural death, and (2) a review of published infant deaths across callitrichids (N = 16), testing for trends in the sex of reacting individuals and cause of death. In our case study, several group members frequently interacted with the dead infant, attempting to carry it. However, the strongest response was from a male that remained with the corpse for ~ 3 h, despite his group leaving the area. Across callitrichid species, corpse interactions were significantly sex-biased: 100% (N = 6) of accidental deaths involved corpse interaction by males (p = 0.007), compared to 60% (N = 3 of 5) by females (p = 0.095). Cause of death also played a significant role, with individuals attempting to carry dead infants in 100% (N = 6) of accidental deaths, but only 11.1% (N = 1 of 9) of infanticides (p = 0.001). Although the available literature is small and potentially subject to publication biases, these data support the idea that visually obvious wounds may influence callitrichids' perception of dead conspecifics. Additionally, male-biased patterns of corpse interaction in callitrichids indicate that social bonds likely shape reactions to the dead, in addition to kinship. While published data on primate thanatology are limited, this study demonstrates quantitative approaches that can provide empirical insights into primates' responses to dead conspecifics. [ABSTRACT FROM AUTHOR]

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Sibling (cousin) correlations are empirically straightforward: they capture the degree to which siblings' (cousins') socioeconomic outcomes are similar. At face value, these quantities seem to summarize something about how families constrain opportunity. Their meaning, however, is complicated. One empirical set of sibling and cousin correlations can be generated from a multitude of distinct theoretical processes. I illustrate this problem in the context of multigenerational mobility: the relationship between the incomes of an ancestor and a descendant separated by several generations in a family. When cousins' outcomes are similar (an empirical fact), prior authors have favored the particular theoretical interpretation that extended kin affect life chances through pathways not involving the parents of the focal individual. I show that this evidence is consistent with alternative theories of latent transmission (measurement error) or dynamic transmission (a parent-to-child transmission process that changes over generations). Theoretical assumptions are required to lend meaning to a point estimate. Further, I show that point estimates alone may be misleading because they can be highly uncertain. To facilitate uncertainty estimation for the key test statistic, I develop a Bayesian procedure to estimate sibling and cousin correlations. I conclude by outlining how future research might use sibling and cousin correlations as effective descriptive quantities while remaining cognizant that these quantities could arise from a variety of distinct theoretical processes. [ABSTRACT FROM AUTHOR]

Measurement creates trustworthy quantifications. But unified frameworks applicable to all sciences are still lacking and discipline-specific terms, concepts and practices hamper mutual understanding and identification of commonalities and differences. Transdisciplinary and philosophy-of-science analyses are used to compare metrologists' structural framework of physical measurement with psychologists' and social scientists' fiat measurement of constructs. The analyses explore the functions that measuring instruments and measurement-executing persons in themselves fulfil in data generation processes, and identify two basic methodological principles critical for measurement. (1) Data generation traceability requires that numerical assignments depend on the properties to be quantified in the study objects (object-dependence). Therefore, scientists must establish unbroken documented connection chains that directly link (via different steps) the quantitative entity to be measured in the study property with the numerical value assigned to it, thereby making the assignment process fully transparent, traceable and thus reproducible. (2) Numerical traceability requires that scientists also directly link the assigned numerical value to known standards in documented and transparent ways, thereby establishing the results' public interpretability (subject-independence). The article demonstrates how these principles can be meaningfully applied to psychical and social phenomena, considering their peculiarities and inherent limitations, revealing that not constructs in themselves but only their indicators (proxies) can be measured. These foundational concepts allow to distinguish measurement-based quantifications from other (subjective) quantifications that may be useful for pragmatic purposes but lack epistemic authority, which is particularly important for applied (e.g., legal, clinical) contexts. They also highlight new avenues for establishing transparency and replicability in empirical sciences. [ABSTRACT FROM AUTHOR]

Using longitudinal data from the No Child Left Behind (NCLB) era, I applied regression techniques and found a positive association between school failure to reach "adequate yearly progress" in mathematics and subsequent changes in the quality of middle grades mathematics instruction in districts where district leaders adopted robust theories of action for improving mathematics instruction. The positive association was robust to multiple sensitivity tests and may reflect a causal relationship. The evidence suggests that educational leaders in similar contexts can use school failure to reach accountability standards as measured by standardized assessments to promote instructional quality in mathematics. [ABSTRACT FROM AUTHOR]

We share here results from a quasi-experimental study that examines growth in students' algebraic thinking practices of generalizing and representing generalizations, particularly with variable notation, as a result of an early algebra instructional sequence implemented across grades 3–5. Analyses showed that, while there were no significant differences between experimental and control students on a grade 3 pre-assessment measuring students' capacity for generalizing and representing generalizations, experimental students significantly outperformed control students on post-assessments at each of grades 3–5. Moreover, experimental students were able to more flexibly interpret variable in different roles and were better able to use variable notation in meaningful ways to represent arithmetic properties, expressions and equations, and functional relationships. This study provides important evidence that young children can learn to think algebraically in powerful ways and suggests that the earlier introduction of algebraic concepts and practices is beneficial to students. [ABSTRACT FROM AUTHOR]

Designing Green Supply Chains (GSCs) requires complex decision-support models that can deal with multiple dimensions of sustainability while taking into account specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM) approaches can be used to quantify trade-offs between economic, social, and environmental criteria i.e. to identify green production options. The aim of this paper is to review the use of MCDM approaches for designing efficient and effective GSCs. We develop a conceptual framework to find relevant publications and to categorise papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that (1) the use of MCDM approaches for designing GSCs is a rather new but emerging research field, (2) most of the publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations, (3) the majority of papers assume all data to be deterministic, (4) little attention has been given to minimisation of waste, (5) numerous indicators are used to account for eco-efficiency, indicating the lack of standards. This study, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with inclusion of uncertainty in parameters that are associated with GSCs. [ABSTRACT FROM AUTHOR]

Generally, democratic regime type is positively associated with participating in international environmental agreements. In this context, this study focuses on the legal nature of an agreement, which is linked to audience costs primarily at the domestic level that occur in case of non-compliance and are felt especially by democracies. Eventually, more legalized (“hard-law”) treaties make compliance potentially more challenging and as democratic leaders may anticipate the corresponding audience costs, the likelihood that democracies select themselves into such treaties decreases. The empirical implication of our theory is that environmental agreements with a larger share of democratic members are less likely to be characterized by hard law. Results from quantitative analyses strongly support our argument, shed new light on the relationship between participation in international agreements and the form of government, and also have implications for the “words-deeds” debate in international environmental policy-making. [ABSTRACT FROM AUTHOR]

Populism is a concept employed to qualify the political behavior of a large number of actors at a worldwide scale, with scientists classifying the latter into populists and non-populists according to dimensions such as ideology, strategy, discourse, economic policy, and even style. This article analyzes existing schools of thought on the nature of populism and argues that conceptualizing populism as a specific type of anti-elite discourse in the name of the People is both conceptually and methodologically the most coherent and useful way to understand the phenomenon. Additionally, it suggests discarding crude, dichotomous classification in favor of a gradated view of populist mobilization by means of quantifying populist discourse and observing its spatial and temporal variation. It adds value to current methods of measurement by demonstrating why and how clause-based semantic text analysis can provide optimal quantitative results while retaining qualitative elements for mixed-methods analysis. Aiming, moreover, at expanding the scope of populism studies by overcoming a narrow view that focuses exclusively at party system developments, it applies semantic text analysis to the study of grassroots mobilization during the Great Recession. Results point to the wide use of populist discourse on the part of movement activists seeking an inclusive language when framing disparate social grievances in a given constituency, a finding with important implications with regards to how populism can facilitate straddling the divide that purportedly distinguishes institutionalized party system behavior from the social movement milieu. [ABSTRACT FROM AUTHOR]

The paper studies a big city as an independent central place system. For this purpose, the author has developed and tested a methodology for quantitative assessment of central functions based on an integrated set of the most important socioeconomic indicators. This methodology helped to prove the possibility of not only measuring the value of central functions in different parts of a big city, but also of determining the affiliation of all the system’s elements with different hierarchical levels or a service area. The study was based on the model of Moscow’s central place system. The study evaluated how the factor of the Russian capital’s considerable territorial expansion has influenced the dynamics of its central place system from 2009 to 2015. We have found that there is a strong interrelation between Moscow’s radial-circular structure and a relatively uniform reduction in the value of central functions with increasing distance from the city center, which is disturbed by the largest highways, which concentrate a significantly higher value of the key factor compared with neighboring elements. [ABSTRACT FROM AUTHOR]

In the presented assay, we elaborated a method for distinguishing sequences that are genetically closely related to each other. This is particularly important in a situation where a fine balance of the allele abundance is a point of research interest. We developed a peptide nucleic acid (PNA) strand invasion technique for the differentiation between multiple sclerosis-associated retrovirus (MSRV) and ERVWE1 sequences, both molecularly similar, belonging to the human endogenous retrovirus HERV-W family. We have found that this method may support the PCR technique in screening for minor alleles which, in certain conditions, may be undetected by the standard PCR technique. We performed the analysis of different ERVWE1 and MSRV template mixtures ranging from 0 to 100% of ERVWE1 in the studied samples, finding the linear correlation between template composition and signal intensity of final reaction products. Using the PNA strand invasion assay, we were able to estimate the relative ERVWE1 expression level in human specimens such as U-87 MG, normal human astrocytes cell lines and placental tissue. The results remained in concordance with those obtained by semi-quantitative or quantitative PCR. [ABSTRACT FROM AUTHOR]

Whether the food movement is most likely to transform the food system through 'alternative' or 'oppositional' initiatives has been the focus of considerable scholarly debate. Alternative initiatives are widespread but risk reinforcing the conventional food system by supporting neoliberal discourse and governance mechanisms, including localism, consumer choice, entrepreneurialism and self-help. While oppositional initiatives such as political advocacy have the potential for system-wide change, the current neoliberal political and ideological context dominant in Canada poses difficulties for initiatives that explicitly oppose the conventional food system. As such, some argue that the food movement requires convergence between alternative and oppositional initiatives. In this paper, we investigate convergence using survey results from 143 food movement organizations in four Canadian provinces. Results based on cluster analysis and descriptive statistics on organizational discourse, activities and visions of sustainable food systems demonstrate convergence around neoliberal discourse and governance mechanisms. Localism and consumer education characteristics are particularly prominent, with a majority of respondents describing their organizations as 'local', engaging in consumer education activities, and stating the importance of consumer education activities, indicating convergence around alternative, rather than oppositional, initiatives. While convergence around these discourse and strategies may limit the transformative potential of the food system when interpreted as neoliberalisation of the movement, such a reading does not demonstrate their full potential, as survey results also indicate trends of transformative visions of change and political engagement, particularly at the municipal level. This research demonstrates that the movement can work simultaneously within, and opposed to, the conventional food system, and provides understanding of both neoliberal leanings and the politics of the possible of the food movement. [ABSTRACT FROM AUTHOR]

This paper proposes a comprehensive new measure of societal quality of life (QOL) at the national level. Focusing on livability, the environmental, external factors that constitute a society's QOL this measure derives from a novel and multifaceted analysis of subjective wellbeing data. In determining what people actually value, the measure allows for a comprehensive cross-country comparison of QOL that complements normative objective-list or capabilities approaches. The analysis supports the five broad categories of Community and Relationships, Freedom and Opportunity, Health and Environment, Living Standard, and Peace and Security as antecedents to QOL. Current measures overlook or deemphasize aspects of these elements. This paper explains the methodology used to construct the index and, provides complete country rankings of QOL for 143 countries since 2000. [ABSTRACT FROM AUTHOR]

Nowadays, urban areas play a crucial role in biodiversity conservation and habitat protection despite the constant pressures on which these habitats are subjected. They may even host relatively new plant communities due to the peculiar ecosystem where they vegetate. The port of Trieste (NE Italy) is characterized by a mixed mosaic of intensely human impacted areas (where commercial activities are still ongoing) flanked by abandoned areas where vegetation persists or has spontaneously recovered. In this study, we sampled the whole port area through a stratified random sampling by placing multiscalar nested plots in four different habitats ( strata) previously identified by photo-interpretation. Plant species richness and abundance were assessed in each plot. Each species was then classified as native or alien and patterns of species richness and complementarity were compared among habitats. Results show that there is a significant difference in species richness patterns among habitats, while observed patterns are likely to vary at different spatial scales. As expected, urban plots account for most of the alien species in the sampling, while wooded plots cope better with invasion, accounting for a lower alien/native ratio. These results highlight how habitat diversity enhances biodiversity in urban areas and how it could provide an effective filtering effect able to reduce the spread of alien species. In addition, we provide further evidence for the use of multi-scale approaches in order to study the complex relationships between spatial heterogeneity and plant species richness. [ABSTRACT FROM AUTHOR]