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To understand human behavior, social scientists need people and data. In the last decade, Amazon’s Mechanical Turk (MTurk) emerged as a flexible, affordable, and reliable source of human participants and was widely adopted by academics. Yet despite MTurk’s utility, some have questioned whether researchers should continue using the platform on ethical grounds. The brunt of their concern is that people on MTurk are financially insecure, subject to abuse, and earn inhumane wages. We investigated these issues with two representative probability surveys of the U.S. MTurk population ( N = 4094). The surveys revealed: (1) the financial situation of people on MTurk mirrors the general population, (2) most participants do not find MTurk stressful or requesters abusive, and (3) MTurk offers flexibility and benefits that most people value above other options for work. People reported it is possible to earn more than $10 per hour and said they would not trade the flexibility of MTurk for less than $25 per hour. Altogether, our data are important for assessing whether MTurk is an ethical place for research.

Machine learning (ML) has been extensively applied in various disciplines. However, not much attention has been paid to data heterogeneity in databases and number of samples used to train ML models in hydrology. In this study, we addressed these issues and their impacts on the accuracy and reliability of ML models in the estimation of saturated hydraulic conductivity, Ks. We selected 17,990 soil samples from the USKSAT database and created random subsets N = 2,000, 4,000, 6,000, 8,000, 10,000, 12,000, 14,000, 16,000, and 17,990, 80% of which were used for training. The random subset selection was repeated 50 times. The extreme gradient boosting (XGBoost) algorithm was used to estimate Ks from other soil properties, such as bulk density, soil depth, texture, and organic content. For each subset, we conducted the learning curve analysis on the training and cross‐validation data sets. Results showed that for all training sample sizes the number of samples was not enough for the training and cross‐validation curves to reach a plateau. We also applied the concept of representative elementary volume by plotting the average coefficient of determination, R2, and root mean square log‐transformed error, RMSLE, against the training sample size. For the testing data set, as the number of training sample size increased from 1,600 to 14,392 the average R2 value increased from 0.74 to 0.90, while the average RMSLE value decreased from 1.08 to 0.69. Either the learning curve or representative sample size analysis is required to investigate whether the number of samples is enough or not. Key Points Learning curves were applied to address effects of data heterogeneity and number of samples on machine learning‐based model estimations Concept of representative elementary volume was used to determine the representative sample size in machine learning The number of samples was not enough for the training and cross‐validation curves to reach a plateau

Background Large sequence datasets are difficult to visualize and handle. Additionally, they often do not represent a random subset of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases. Results Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity. Conclusions Treemmer can reduce the size of datasets with different phylogenetic structures and levels of redundancy while maintaining a sub-sample that is representative of the original diversity. Additionally, it is possible to fine-tune the behavior of Treemmer including any kind of meta-information, making Treemmer particularly useful for empirical studies.

The primary objective of this work is to improve our understanding of the scale effect of the joint shear behavior. Attempts are made to combine different proposed methods with the multiscale joint shear test. First, a new type of rock-like material made from a mixture of raw materials is used to simulate rock joints. Then a new sampling method is used with the progressive coverage statistical method for the representative sampling of actual joints, and an inverse controlling technology is designed with an invented series of multiscale molds for the construction of a similar surface model in series scale (100 mm × 100 mm to 1000 mm × 1000 mm). Finally, the independently developed multiscale direct shear tester is used to measure the shear behavior of joint replicas. The quality of results shows the capacity of this experimental technology in investigating the scale effect of the joint shear behavior.

Background: Health literacy (HL) is perceived as one of the most important concepts for modern health promotion activities to be successful. The research undertaken in the context of HL usually focuses on its antecedents and consequences, either for specific groups of patients or society or for the whole population. Objectives: The main aim of this study was to assess the antecedents and consequences of limited health literacy (HL) in a nationally representative sample of the Polish population. Methods: The analysis was carried out on the data obtained from a sample of 1000 Polish citizens through a telephone-based survey undertaken using a short, 16-item questionnaire developed within the European Health Literacy Project (HLS-EU). The total HLS score was calculated according to the guidelines published by the HLS-EU project. Chi2 test and logistic regression models were used for the analysis of the relationships between the variables. Results: The mean HL score (standard deviation) in the study sample was 12.99 (3.11). HL was related to age, marital and vocational status. Limited HL was associated with a lower self-assessment of health (OR, 95% CI: 2.52, 1.54–4.13), the prevalence of obesity and disability (1.71, 1.13–2.57, and 1.92, 1.25–2.94, respectively), less frequent physical activity (0.70, 0.49–0.99), a lower consumption of fruits and vegetables (0.47, 0.34–0.65), and with more frequent hospitalisations (2.02, 1.38–2.95). Conclusions: The assessment of HL using the16-item HLS-EU questionnaire may be a useful tool to enable health behaviours and utilisation of health care resources by society to be predicted.

Background There is still a lack of systematic investigation of comprehensive contextual factors of subjective well-being (SWB) among Chinese oldest-old. This study aimed to explore sociodemographic, health-related, and social predictors of SWB among Chinese oldest-old using a large and representative sample. Methods The study included 49,069 individuals aged 80 and older from the Chinese Longitudinal Healthy Longevity Survey, a prospective, nationwide, community-based study conducted from 1998 to 2014. SWB was measured by eight items covering life satisfaction, positive affect (optimism, happiness, personal control, and conscientiousness), and negative affect (anxiety, loneliness, and uselessness). Generalized estimating equation models were used to explore the predictors of SWB. Results We found that age, gender, ethnic group, education, primary occupation before retirement, current marital status, and place of residence were sociodemographic predictors of SWB among the Chinese oldest-old. The health-related predictors included self-rated health, visual function, hearing function, diet quality, smoking status, drinking status, and exercise status. SWB was influenced by some social factors, such as the number of biological siblings, the number of children, leisure activities, financial independence, and access to adequate medical service. In particular, self-rated health, access to adequate medical services, exercise status, and place of residence exert a stronger effect than other factors. Conclusions SWB in the oldest-old is influenced by a large number of complex sociodemographic, health-related, and social factors. Special attention should be paid to the mental health of centenarians, women, rural residents, widowed, physically disabled, and childless oldest-old people. Relevant agencies can improve physical activities, leisure activities, financial support, and medical services to promote the well-being of the oldest-old.

We provide a review of the literature related to the “wrong skewness problem” in stochastic frontier analysis. We identify two distinct approaches, one treating the phenomenon as a signal from the data that the underlying structure has some special characteristics that allow inefficiency to co-exist with “wrong” skewness, the other treating it as a sample-failure problem. Each leads to different treatments, while siding with either raises certain methodological issues, and we explore them. We offer simulation evidence that the wrong skewness as a sample problem likely comes from how the noise component of the composite error term has been realized in the sample, which points towards a new way to handle the problem. We also investigate the issues that arise when attempting to use the unconstrained Normal-Half Normal (Skew Normal) likelihood.

A fundamental assumption of many ecological studies is that researchers are studying a representative sample of the population of interest. However, fish and wildlife studies, including many telemetry studies, often rely upon data from marked individuals that are sampled opportunistically rather than randomly and may provide little information on unmarked individuals. Data that are unrepresentative at the time of marking may need to be censored until marked animal distributions are representative of the population. In the absence of additional data on unmarked individuals, evaluating the representativeness of newly marked individuals within a population of interest can be difficult. If previously marked individuals can be assumed to be spatially representative of the population, comparing the spatial distributions of different cohorts of marked individuals can provide an alternative means to assess the representativeness of newly marked animals. We used simulations to assess the effectiveness of a randomization test that compared the spatial distribution between newly marked and previously marked individuals as an alternative to recapture-based methods for evaluating mixing of newly marked individuals with the population of interest and compared different metrics of spatial overlap. We then testedthis randomization test on radio-collared caribou (Rangifer tarandus) from 2 different herds with very different marking strategies. We found that, based on simulation results, kernelbased metrics outperformed cluster analysis metrics and that Bhattacharyya's Affinity (BA) index of kernel overlap was a good metric to identify differences in spatial distribution between marked cohorts. The time it took for newly marked caribou to become mixed with previously marked animals was primarily related to the timing of marking in relation to seasonal movement patterns (periods of aggregation and dispersion, and seasonal differences in spatial fidelity) and the spatial distribution of marking relative to seasonal distribution. In some cases, mixing did not occur until calving aggregations formed in early June. We recommend that researchers evaluate the assumption that marked individuals are spatially representative of their study population and carefully assess sampling time and location of their marking program to increase the likelihood that marked individuals represent the population of interest.

Life Satisfaction is a key indicator of subjective well-being and represents its cognitive component, measuring individuals’ judgment of their own lives. The aim of this study is to analyze the predictors of Life Satisfaction in a large Italian representative sample. To this end, we consider sociodemographic characteristics and other variables identified in the literature as central to Life Satisfaction. These variables are satisfaction with standards of living, household income satisfaction, positive affect, negative affect, and social support. Cross-sectional. The data were extracted from the Gallup World Poll which has collected nationally representative samples from Italy since 2005. The total number of participants was 14,039 individuals aged 15 and above (58.3% females, Mage = 48.74, SDage = 16.43). The results show that women score significantly lower than men on Life Satisfaction and that Life Satisfaction declines with age. Furthermore, satisfaction with standards of living is the strongest predictor of Life Satisfaction. Household income satisfaction, positive affect, social support, and negative affect, respectively, follow. Present findings demonstrate that researchers and policy-makers need to pay attention to a wide range of economic and psycho-social factors in order to understand and improve Life Satisfaction in Italy.

Aflatoxin contamination in corn is a significant issue, posing substantial health threats to humans and animals. Aflatoxin testing protects consumer health, ensures the safe global trade of corn, and verifies compliance with legislation; however, effective sampling procedures are essential to ensure reliable results. While many sampling procedures exist, there is no evidence to indicate which is the best approach to ensure accurate detection. Using scientific and gray literature sources, this review analyzed sampling procedures to determine an optimum approach to guide the development of standard practices. Results revealed that sampling is the major source of error in the accurate assessment of aflatoxin levels in food and crucial for obtaining reliable results. To guarantee low variability and sample bias-increased sample size and sampling frequency, the use of automatic dynamic sampling techniques, adequate storage, and homogenization of aggregate samples for analysis are advised to ensure a representative sample. However, there is a lack of evidence to support this or indicate the current utilization of the reviewed procedures. Inadequate data prevented the recommendation of sample sizes or frequency for optimum practice, and thus, further research is required. There is an urgent need to make sampling procedures fit-for-purpose to obtain accurate and reliable aflatoxin measurements.