Greater Explanatory Power Research Articles

Inadequacies in the SES–Achievement model: Evidence from PISA and other studies

AbstractStudents’ socioeconomic status (SES) is central to much research and policy deliberation on educational inequalities. However, the SES model is under severe stress for several reasons. SES is an ill‐defined concept, unlike parental education or family income. SES measures are frequently based on proxy reports from students; these are generally unreliable, sometimes endogenous to student achievement, only low to moderately intercorrelated, and exhibit low comparability across countries and over time. There are many explanations for SES inequalities in education, none of which achieves consensus among research and policy communities. SES has only moderate effects on student achievement, and its effects are especially weak when considering prior achievement, an important and relevant predictor. SES effects are substantially reduced when considering parent ability, which is causally prior to family SES. The alternative cognitive ability/genetic transmission model has far greater explanatory power; it provides logical and compelling explanations for a wide range of empirical findings from student achievement studies. The inadequacies of the SES model are hindering knowledge accumulation about student performance and the development of successful policies.Context and implicationsRationale for this studyThis review was written in response to the disconnect between the literature surrounding student achievement studies, and the cognitive psychology and behavioural genetic academic literatures. It is well‐established that student achievement is closely related to cognitive ability and both have sizable genetic components, findings largely ignored in achievement studies. This review’s aim is for more considered responses to socioeconomic inequalities in student achievement by both researchers and policymakers.Why the new findings matterThe review provides overwhelming evidence that much of the current thinking about SES and student achievement is mistaken.Implications for researchers and policymakersThe current emphasis on SES is misleading and wastes considerable human and financial resources that could much better be utilized. The focus should be on student performance ensuring that low achievers have rewarding educational and occupational careers, and raising the overall skill levels of students, not on the nebulous, difficult to measure, concept of SES, which is only moderately associated with achievement.

Stratifying for Value: An Updated Population Health Risk Stratification Approach.

Most risk stratification approaches attempt to predict clinical outcomes rather than value. For a provider organization or health system to have financial success in value-based contracting, future risk models must analyze costs as well as disease burden. The purpose of this study was to create a customized risk stratification algorithm that considered a patient's medical spend alongside disease burden while delivering a scoring system that improves the efficiency of a care coordination program. The authors focused on University Hospitals (UH) Health System's Accountable Care Organization population of 554,805 because this patient cohort is engaged with UH's primary care network and has the most robust data. The 5-category risk algorithm was found to be meaningful and impactful after integrating the foundation of the Minnesota Tiering system with an expanded comorbidity list and weighting the result by the previous 12 months of medical spend. This new technique can identify patients in need of intensive care coordination. The complex risk tier of the stratification system reduces the number of patients from 551,045 to 27,552, or 5% of the patient population, and accounts for 67.9% ($1,107,822,887) of total annual medical spend. Expanding care coordination efforts to patients in the top 2 tiers would account for 15% of the patients and 83.2% ($1,357,545,872) of annual medical spend. The novelty of the new approach allows clinical teams to focus intense resources on a smaller sample of the patient population and to identify chronic conditions contributing to costs, and feel confident that they have greater explanatory power regarding value.

Monitoring, analyzing and predicting urban surface subsidence: A case study of Wuhan City, China

Wuhan, one of China's megacities with rapid development, is facing serious surface subsidence. In this study, we combined MT-InSAR, geo-detector, and LSTM (Long Short-Term Memory) to achieve the monitoring, analysis, and prediction of surface subsidence in the main urban districts of Wuhan. The effectiveness of MT-InSAR in monitoring surface subsidence was validated against leveling results. During the monitoring period, the maximum subsidence velocity and uplift velocity were −53.3 mm/year and 18.0 mm/year, respectively. We identified six subsidence regions and explored their deformation characteristics. Further, we analyzed the relationship between the surface subsidence and influencing factors using the geo-detector in a quantitative manner. Our study revealed that the distance to soft soils had the greatest explanatory power on the subsidence. However, we also confirmed that subsidence was affected via coupling effects from multiple factors, suggesting a complex reinforcing relationship among influencing factors. The interaction between the distance to soft soils and the distance to karst collapse prone areas had the largest joint explanatory power on subsidence. Further, we constructed a data-driven LSTM model to predict and analyze the subsidence. The results showed that the LSTM model achieved great performance and presented strong universality, suggesting that it can be used for subsidence prediction in large geographic areas.

Momentum or reversal: Which is the appropriate third factor for cryptocurrencies?

Shen et al. (2020) propose a three-factor pricing model for cryptocurrencies by including market, size, and reversal factors. However, evidence from cryptocurrencies during a more recent sample period suggests the existence of a momentum effect rather than a reversal effect. Consequently, we introduce and test a three-factor pricing model including market, size, and momentum factors (MSM three-factor model). This MSM three-factor model outperforms the quasi-cryptocurrency CAPM (Q-C-CAPM) of Shen et al. (2020), with greater explanatory power.

Comparative Analysis and Empirical Testing of Major Theories’ Contextual Fits in the Medical Tourism Field

Purpose - The medical tourism industry is recognized as one of the most promising industries in Korea. Identifying the factors affecting foreign medical tourist purchasing behaviors has become increasingly important to the industry’s sustainable development. In the field of medical tourism, major approaches adopted to explain medical tourist purchasing intentions can be categorized into three groups: the rational choice model, the socio-cultural approach, and the institutional approach. The first purpose of this study is to compare these three theories, and to examine which has greater explanatory power in describing medical tourist behaviors. The second purpose is to find the contextual fit, or the context each theory fits well. Design/Methodology/Approach - Key constructs for each model are developed to compare the explanatory power of the three approaches (the rational choice model, the socio-cultural approach, and the institutional approach). To examine how medical tourist personal characteristics impose restrictions on the scope of the explanation of the three approaches, three constructs (innovativeness, Internet search competence, and gender) were introduced as moderating variables. The relationship between independent variables and dependent variable (purchasing intention) may or may not be affected by the moderating variables. Findings - Judging from hypotheses testing, it can be roughly said that the socio-cultural approach is the most explanatory, followed by the rational choice model and the institutional approach. The rational choice model fits well when medical tourists are innovative, competent at Internet searches, and male. The socio-cultural approach fits less or poorly when medical tourists are innovative and competent at Internet searches. The institutional approach fits less when tourists are competent at Internet searches. Research Implications - Three major theories in the field of medical tourism have not been empirically compared to see which has greater explanatory power in describing medical tourist behaviors. The attempt to find the major theories’ contextual fits is a kind of investigation that is rare and pioneering in this area of research. This study’s findings are expected to facilitate a similar kind of research.

Impacts of climate change and anthropogenic activities on vegetation change: Evidence from typical areas in China

Understanding the interactions of climate-vegetation and human-vegetation has been a critical issue and increasingly attracting attention from scientific community in the field of global change research. This study investigated the heterogeneous impacts of climate change and anthropogenic activities on vegetation change by applying the trend analysis and Geodetector approach. The spatial and temporal patterns of MODIS NDVI and LAI during 2003–2017 were firstly examined in China. We then quantified the contribution and interactions effects of climatic factors (temperature and precipitation) and anthropogenic factors (population, gross domestic product and other four categories of forestry investment) on vegetation change in five typical areas of China. Both NDVI and LAI across China demonstrated a significant increasing trend over the past two decades. However, the eastern developmental regions such as Beijing-Tianjin-Hebei Region and Yangtze River Delta exhibited a decreasing trend due to fast urbanization. Socio-economical inputs (the explanatory power of forestry investment > 40%, the range of explanatory power is 0 to 100%) were identified as the dominant driving forces of vegetation change for the most of study areas. Precipitation was the most important natural influencing factor of vegetation change. We also found that the interactions between forestry investment and other factors presented much greater explanatory power on vegetation change than a single factor. Our research highlights that the afforestation program in China during the past several decades plays an important role in contributing to vegetation greening across the country. Greening and degradation, however, are largely related to landscape context, which could be due to natural change and anthropogenic impact. To maintain high levels of forests, conserving the vegetation is more important than increasing the economic development.

Information Order for Periviable Counseling: Does It Make a Difference?

To examine whether the order of presenting survival vs disability information, with or without the description of infant neonatal intensive care unit (NICU) experiences would influence treatment choice during hypothetical periviable birth counseling. An internet sample of childbearing-aged women (n=839) viewed a pictograph displaying the chances of survival and a pictograph on the chances of disability for a baby resuscitated during the periviable period. The sample was randomized to the order of pictographs and level of description of infant NICU experiences. Participants selected between intensive care or comfort care and reported their personal values. The order of the information influenced treatment choices (P=.02); participants were more likely to choose intensive care if they saw the survival pictograph first (70%) than the disability pictograph first (62%). Level of description of premature infant NICU experiences did not influence treatment choice (P=.92). Participants who valued sanctity of life, autonomy in making decisions, who were more religious, and had adequate health literacy were more likely to choose intensive care. Such participant characteristics had greater explanatory power than the experimental manipulations. Subtle differences in how information is presented may influence critical decisions. However, even among women with the same values, diversity in treatment choice remains.

Influence of the health status and other relevant factors on the quality of life of elderly people

Background/Aim. The world population is aging rapidly. It has become a challenge to meet the vital needs of the elderly in big cities. The aim of the study was to investigate the influence of the health status as well as other relevant factors on the perceived quality of life in aged people in Belgrade, Serbia. Method. The survey was conducted in October 2019 on a representative sample of 764 people (39.9% male and 60.1% female) aged between 65 and 79 years (mean ? standard deviation = 72.68 ? 7.11 years) living in Belgrade. In the research, a questionnaire developed on the basis of the World Health Organization (WHO) methodology for age-friendly cities was used, aimed to explore 11 factors important for the elderly. Results. Factor of physical accessibility of community and socioeconomic factors were highly significant [?2 (df = 3, n = 764) = 238.905; p < 0.001 and ?2 (df = 3, n = 764) = 207.571; p < 0.001, respectively] and explained 39.4% and 35% of variance of perceived quality of life, respectively. Social environment explained 24.6% of variance of perceived quality of life [?2 (df = 4, n = 764) = 140.242; p < 0.001]. Health sta-tus had greatest explanatory power regarding perceived quality of life and explained as much as 46.7% of variance [?2 (df = 8, n = 764) = 292.083; p < 0.001]. When the unique impact of health status on quality of life was analyzed, when other variables were controlled, health status explained 21.6% of the variance in addition to the variance explained by physical accessibility, socioeconomic status, and social environment. Conclusion. Although health status has the greatest impact on the perceived quality of life of older people, interventions on other life important domains such as physical accessibility, socioeconomic status, and social environment could have a positive impact on the perceived quality of life where health status alone could not be improved.

A Marxian Reply to Hahnel: The Relative Explanatory Power of Marx’s Theory and Sraffa’s Theory

This paper critically examines Robin Hahnel’s 2017 book Radical Political Economy: Sraffa versus Marx and especially compares the relative explanatory power of Marx’s theory and Sraffa’s theory. Hahnel’s book argues that Sraffa’s theory is superior to Marx’s theory with respect to the following six subjects: prices, profit, technological change, crises, the environment, and moral critique (each one considered in a separate chapter). This paper challenges Hahnel’s arguments on all six subjects and argues that Marx’s theory has greater explanatory power than Sraffa’s theory and continues to be the best critical theory of capitalism. JEL Classification: B24, B51

Socially Oriented Shareholder Activism Targets: Explaining Activists’ Corporate Target Selection Using Corporate Opportunity Structures

We examine whether and when socially oriented shareholder activists use firms’ corporate social performance (CSP) to identify them as attractive targets for their activism. We build on the research in social movements theory and stakeholder theory to theorize how firms’ engagement with primary and secondary stakeholders reflected in their technical and institutional CSP respectively allows socially oriented shareholder activists to identify targets. We develop a theoretical model by identifying corporate targets’ degree of (1) receptivity to and (2) need to comply with activist demands as two key dimensions of their corporate opportunity structure that explains the variance in firms’ attractiveness as targets for activist demands. We show that a firm’s technical and institutional CSP independently affect the likelihood of activists targeting the firm. We also show that our model has greater explanatory power at firms with high resource slack and from activists not identifying as socially responsible investment funds. Analysis of CSP and shareholder proposals data of 992 U.S. public firms over an 8-year window of observation largely supports our theory.

Genomic signatures of drift and selection driven by predation and human pressure in an insular lizard

Genomic divergence was studied in 10 small insular populations of the endangered Balearic Islands lizard (Podarcis lilfordi) using double digest restriction-site associated DNA sequencing. The objectives were to establish levels of divergence among populations, investigate the impact of population size on genetic variability and to evaluate the role of different environmental factors on local adaptation. Analyses of 72,846 SNPs supported a highly differentiated genetic structure, being the populations with the lowest population size (Porros, Foradada and Esclatasang islets) the most divergent, indicative of greater genetic drift. Outlier tests identified ~ 2% of loci as candidates for selection. Genomic divergence-Enviroment Association analyses were performed using redundancy analyses based on SNPs putatively under selection, detecting predation and human pressure as the environmental variables with the greatest explanatory power. Geographical distributions of populations and environmental factors appear to be fundamental drivers of divergence. These results support the combined role of genetic drift and divergent selection in shaping the genetic structure of these endemic island lizard populations.

Multi-scale assessment of distribution and density of procellariiform seabirds within the Northern Antarctic Peninsula marine ecosystem

Abstract The Antarctic Peninsula is one of the most rapidly warming regions on earth, and it is likely that the abundance and distribution of marine predators will change as a result.Procellariiform seabirds are highly mobile predators, which target specific habitat characteristics associated with underlying distributions of prey and areas of increased prey availability. We use ship surveys and hurdle models, to estimate the summer distribution and relative density of 11 seabird species within the northern Antarctic Peninsula marine ecosystem. Models differed among species; however, sea surface temperature and depth were frequently associated with seabird occurrence and had the greatest explanatory power across many species. Null models based on observation data were better at predicting seabird density than models that included environmental covariates. This suggests that the main driver of distribution patterns is the broad-scale habitat features, and fine-scale aggregations within these ranges are harder to predict. Our seabird distribution models reflect known habitat associations, species hotspots, and community organization relative to oceanic and coastal marine processes. Application of species distribution models will benefit the assessments of critical habitat and potential responses to climate change and anthropogenic disturbance, which will provide insight into how species may change in polar ecosystems.

Meaning in Life: A Major Predictive Factor for Loneliness Comparable to Health Status and Social Connectedness.

Objective: Loneliness is the subjective distress of feeling alone and has a strong impact on wellbeing and health. In addition to well-known predictors like isolation and poor health, a better understanding of the psychological determinants of loneliness would offer effective targets for future complementary interventions.Methods: In this cross-sectional observational study (N = 2,240), we compared the explanatory power of several important risk factors of loneliness with the affective, motivational, and cognitive aspects of the Meaning in Life (MiL) construct. Different nested linear models were compared including socio-demographic, lifestyles, social-connectedness, and self-rated health variables, to assess the overlapping and non-overlapping explanatory power of each of them.Results: Health status and MiL were found to be the most important predictors of loneliness, followed by social connectedness and, with a much lower weight, lifestyles, and socio-demographic factors. Within the MiL factor, the most cognitive component, sense of coherence, had a greater explanatory power than the more affective and motivational ones.Conclusion: Reduced MiL, the capacity of an individual to attach “value and significance” to life, is a crucial predictor to the feeling of loneliness. These results suggest that programs aiming to combat loneliness should go well beyond situational interventions and include more cognitive, value-centered interventions that enable individuals to define and pursue a meaningful vital plan.

Estimation of Travel Mode Choice Using Geostatistics: a Brazilian Case Study

Traditional methods for travel demand estimation are often built on socioeconomic and travel information. The information required to conduct such studies is costly and rarely available in developing countries. Besides, some conventional methods do not consider the spatial relationship of variables and, in general, a large amount of socioeconomic and individual travel data is required. The key aim of this paper is to evaluate the importance of considering spatial information when estimating travel mode choices especially considering the lack of available data. The study area is the São Paulo Metropolitan Area (Brazil) and the dataset refers to an Origin-Destination Survey, conducted in 2007. This research paper analyzes the use of Geostatistics when estimating discrete travel mode choices. The results demonstrated a satisfactory outcome for the geostatistical approach. Finally, although socioeconomic and travel variables have greater explanatory power in predicting travel mode choices, spatial factors contribute to better understand the travel behavior and to provide further information when estimating spatially correlated data.

Catastrophic cognitions about coronavirus: the Oxford psychological investigation of coronavirus questionnaire [TOPIC-Q

Cognitive therapies are developed on the principle that specific cognitive appraisals are key determinants in the development and maintenance of mental health disorders. It is likely that particular appraisals of the coronavirus pandemic will have explanatory power for subsequent mental health outcomes in the general public. To enable testing of this hypothesis we developed a questionnaire assessing coronavirus-related cognitions. 12 285 participants completed online a 46-item pool of cognitions about coronavirus and six measures of different mental health problems. The sample was randomly split into derivation and validation samples. Exploratory factor analyses determined the factor structure, selection of items, and model fit in the derivation sample. Confirmatory factor analysis (CFA) then tested this model in the validation sample. Associations of the questionnaire with mental health outcomes were examined. The 26-item, seven-factor, Oxford Psychological Investigation of Coronavirus Questionnaire [TOPIC-Q] was developed. CFA demonstrated a good model fit (χ2 = 2108.43, df = 278, p < 0.001, comparative fit index (CFI) = 0.950, Tucker-Lewis index (TLI) = 0.942, root mean square error of approximation (RMSEA) = 0.033, standardized root mean square residual (SRMR) = 0.038). The factors were: cognitions about (1) safety and vulnerability, (2) negative long-term impact, (3) having the virus, (4) spreading the virus, (5) social judgment, (6) negative self, and (7) being targeted. The questionnaire explained significant variance in depression (45.8%), social anxiety (37.3%), agoraphobia (23.2%), paranoia (27.3%), post-traumatic stress disorder (57.1%), and panic disorder (31.4%). Cognitions about negative long-term impact had the greatest explanatory power across disorders. TOPIC-Q provides a method to assess appraisals of the pandemic, which is likely to prove helpful both in longitudinal studies assessing mental health outcomes and in delivery of psychological therapy.

Values and personality traits as predictors of Catholic religiosity

The main goal of this study was to investigate the dimensions of value orientations and personality traits that underly Catholic religiosity. The survey was carried out on a convenient adult sample of members of the Croatian ethnic minority across the Autonomous Province of Vojvodina in the Republic of Serbia (N = 189); 97% were members of the Roman Catholic Church. Four measures were included in the questionnaire: Religiosity, the Schwartz Value Scale, the Big Five Personality Inventory, and the Dark Triad of Personality. Multiple regression analyses were conducted to explore how value orientation and personality traits impact religiosity. Conservation (Traditional) values and Self-Transcendence values emerged as significant positive predictors, whereas Openness to Change values emerged as a significant negative predictor of religiosity. Agreeableness and Conscientiousness emerged as significant positive predictors, whereas Extraversion emerged as a significant negative predictor of religiosity. Machiavellianism and Psychopathy were also shown to be significant negative predictors of religiosity; in order, Psychopathy, Machiavellianism, and Conservation values accounted for 23% of the variance in Catholic Religiosity. We found that the Schwartz value orientations had a somewhat greater explanatory power than the Big Five personality traits, and that the Dark Triad of personality traits had a greater explanatory power in predicting Catholic religiosity than either the Schwartz value orientations or the Big Five personality traits. We argued that religiosity is not generally more correlated with values than with personality traits, as is often suggested. It depends primarily on the type of personality trait models involved, i.e. its psychopathological underpinning.

Comparison between static modulus of elasticity, non-destructive testing moduli of elasticity and stress-wave speed in white spruce and lodgepole pine wood

ABSTRACT Static bending tests to measure modulus of elasticity (MOEST) or wood stiffness provide an indicator of the structural performance of a finished product. These tests are however, slow and expensive. Tests to measure MOE using non-destructive testing (NDT) provide alternatives to MOEST tests; however, relationships between the different modes of measurement need to be established. Non-destructive testing MOE measured by two methods (SilviScan [MOESS] and time of flight [MOETOF]) have been compared with MOEST for lodgepole pine and white spruce. The relationships between stress wave speed (SWS) and MOEST have also been evaluated. Simple linear regressions of MOESS, MOETOF, and SWS had greater explanatory power (higher coefficients of determination (R2)) than did multiple linear regressions including growth rate or other wood fibre attributes. Simple linear regression from MOETOF and MOESS on MOEST had lower R2 for lodgepole pine than for white spruce; however, the converse was true for SWS. SWS had the highest R2 (89%) and MOESS the lowest R2 (47%) when regressed on MOEST in lodgepole pine. The results were tool and species specific, suggesting that R2 between MOEST and non-destructive testing MOE values must be validated separately for each commercial tree species and for each measurement technique.

Acceptability of mobile stock trading application: A study of young investors in Malaysia

Mobile financial services have been adopted rapidly during the digitisation era. This study therefore aims to investigate the antecedents of mobile stock trading adoption among young investors. Using the structural equation modelling technique, this study develops an integrated theoretical framework from both the Technology Acceptance Model and Theory of Planned Behaviour using survey data from 373 young retail investors. The suggested model incorporates the six constructs of perceived risk, perceived benefits, perceived usefulness, attitude, perceived behavioural control and social influence and assesses how they affect the intention to adopt mobile stock trading. The results show a strong positive connection among attitude, perceived behavioural control, perceived benefits and intention towards mobile stock trading. We find that trust adds great explanatory power to perceived behavioural control, attitude and social influence in explaining investors’ adoption intention. Surprisingly, perceived risk is not significantly correlated with adoption intention. This study has employed a comprehensive framework to understand the acceptance level of mobile stock trading.

Evolutionary time best explains the latitudinal diversity gradient of living freshwater fish diversity

AbstractAimThe evolutionary causes of the latitudinal diversity gradient are debated. Hypotheses have ultimately invoked either faster rates of diversification in the tropics or more time for diversification owing to the tropical origins of higher taxa. Here, we perform the first test of the diversification rate and time hypotheses in freshwater ray‐finned fishes, a group comprising nearly a quarter of all living vertebrates.LocationGlobal.Time period368–0 Ma.Major taxa studiedExtant freshwater ray‐finned fishes.MethodsUsing a mega‐phylogeny of actinopterygian fishes and a global database of occurrence records, we estimated net diversification rates, the number of colonizations and regional colonization times of co‐occurring species in freshwater drainage basins. We used generalized additive models to test whether these factors were related to latitude. We then compared the influence of diversification rates, numbers of colonizations, colonization times and surface area on species richness, and how these factors are related to each other.ResultsAlthough both diversification rates and time were related to richness, time had greater explanatory power and was more strongly related to latitude than diversification rates. Other factors (basin surface area and number of colonizations) also helped to explain richness but were unrelated to latitude. The most diverse freshwater basins of the world (Amazon and Congo rivers) were dominated by lineages having Mesozoic origins. The temperate groups dominant today arrived near the Cretaceous–Palaeogene boundary, leaving comparatively less time to build richness. Diversification rates and colonization times were inversely related: recently colonized basins had the fastest rates, whereas ancient species‐rich faunas had slower rates.Main conclusionsWe concluded that time is the leading driver of latitudinal disparities in richness in freshwater fish faunas. We suggest that the most likely path to building very high species richness is through diversification over long periods of time, rather than through rapid diversification.

Determining factors of the intention to adopt fintech services by micro and small business owners from Chiclayo, Peru

The objective of this research was to determine the factors that influence the intention to adopt fintech services by micro and small business owners from Chiclayo; for this purpose, an applied quantitative study was carried out in which the extended technology acceptance model proposed by Hu, Ding, Li, Chen and Yang (2019) was used for the analysis of nine variables related to the adoption of these technologies. The results reaffirmed that most of the constructs included in the conceptual model have great explanatory power regarding the adoption intention of fintech services, in that 11 of the 13 hypotheses were proven. Thus, it was demonstrated that business owners from Chiclayo use a new technology mainly under the influence of factors such as trust, brand image, and perceived utility, while also considering the potential risks to which they may be exposed; together, these considerations influence their attitude toward adopting fintech services. Finally, the analysis showed that government support and perceived ease of use have only a limited effect, while user innovativeness was the only factor that turned out to be non-significant in the intention to adopt this kind of services.