“岂不怀匡济,天运当何如”──论天然禅师的安攘匡济情怀与通脱的应世方式

清初岭南佛门领袖天然禅师,年轻时抱有强烈的报国安民的情怀。虽然在明亡之前即已剃度,但安攘济世之心并未泯灭。甲申、乙酉之后,身为僧人的他,并未真正弃绝世事。他的一些行为仍与变乱的时局密切相关。其后,他在诗歌中不断地抒写着故国丘墟之感。其沧海桑田之作俨然前明遗民。尽管如此,他并没有拒绝与新朝官员的交接。甚至其诗歌中还有一些肯定新朝官员的作品。可以看出天然禅师在应世方式上是相当通脱的。     

秦汉礼制中渗透的神学观念——以河北地区为例

秦汉时期,是宗教与封建专制融合的时代,以方术、巫术为基础的宗天神学和谶纬神学得到统治者推崇,对秦汉政治、文化产生了深刻的影响,甚至秦汉时期许多封建礼制和典章制度,都源于方术及其相关的宗教信仰。而河北地区的燕赵故地,正是神学宗教盛行的地区。以大量史实为基础,研究秦汉礼制中蕴含的神学宗教,可剖析封建礼制与宗教的关系和相互作用。     

Exploring gaps in the online economic inclusion of persons with disabilities in Korea

ABSTRACT

This paper explores the difference in the online economic activities of people with and without disabilities in Korea. We conducted a multiple regression analysis to investigate the impact of socioeconomic characteristics, internet access, and internet skills on online economic activities. Our sample, based on a 2016 dataset that included 1554 people with disabilities and 6004 people without disabilities, was developed using quota sampling based on gender, age, and residence. We determined that individuals with disabilities were more likely to engage in online economic activities if they had higher levels of education, lived in urban areas, were employed, or had greater internet skills. Individuals without disabilities were more likely to engage in online economic activities if they were women, had higher levels of education, were employed, lived in a two-generation or more household, or had greater internet skills. For both people with and without disabilities, the level of education, employment status, and internet skills positively contribute to online economic activites. We also determined that education level, participation in economic activity, living in a two-generation or more household, and internet skills had a statistically significant influence on online economic activity for people both with and without disabilities. These results highlight the importance of education and internet training for people with disabilities, as well as social support systems that help them learn to use the internet in diverse ways through both formal and informal networks. The study also underscores the importance of information and communications technology that adequately addresses people’s needs.     

Perceptions of Randomized Security Schedules

Security of infrastructure is a major concern. Traditional security schedules are unable to provide omnipresent coverage; consequently, adversaries can exploit predictable vulnerabilities to their advantage. Randomized security schedules, which randomly deploy security measures, overcome these limitations, but public perceptions of such schedules have not been examined. In this experiment, participants were asked to make a choice between attending a venue that employed a traditional (i.e., search everyone) or a random (i.e., a probability of being searched) security schedule. The absolute probability of detecting contraband was manipulated (i.e., 1/10, 1/4, 1/2) but equivalent between the two schedule types. In general, participants were indifferent to either security schedule, regardless of the probability of detection. The randomized schedule was deemed more convenient, but the traditional schedule was considered fairer and safer. There were no differences between traditional and random schedule in terms of perceived effectiveness or deterrence. Policy implications for the implementation and utilization of randomized schedules are discussed.     

A Method to Handle Zero Counts in the Multinomial Model

In the context of an objective Bayesian approach to the multinomial model, Dirichlet(a, …, a) priors with a < 1 have previously been shown to be inadequate in the presence of zero counts, suggesting that the uniform prior (a = 1) is the preferred candidate. In the presence of many zero counts, however, this prior may not be satisfactory either. A model selection approach is proposed, allowing for the possibility of zero parameters corresponding to zero count categories. This approach results in a posterior mixture of Dirichlet distributions and marginal mixtures of beta distributions, which seem to avoid the problems that potentially result from the various proposed Dirichlet priors, in particular in the context of extreme data with zero counts.     

“A stitch in time”: group work during the covid-19 scare in the Nicobar Islands,India

ABSTRACT

When India suddenly went into its first coronavirus-induced nationwide lockdown in March 2020, several members of a historically isolated indigenous community in the eastern Indian ocean- the Nicobarese, began to panic. Their leaders came together and formed a group to boost community solidarity and helped the vulnerable indigenes to safely navigate through the crisis. In these uncertain times of Covid-19, when the “modern” world appears more fissured than ever, leaving its “others” to fend for themselves; the Nicobarese’s group has set an example for everyone to follow.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Interactive Hazards Education Program for Youth in a Low SES Community: A Quasi‐Experimental Pilot Study

A pilot study of an interactive hazards education program was carried out in Canberra (Australia), with direct input from youth participants. Effects were evaluated in relation to youths’ interest in disasters, motivation to prepare, risk awareness, knowledge indicators, perceived preparedness levels, planning and practice for emergencies, and fear and anxiety indicators. Parents also provided ratings, including of actual home‐based preparedness activities. Using a single group pretest‐posttest with benchmarking design, a sample of 20 youths and their parents from a low SES community participated. Findings indicated beneficial changes on a number of indicators. Preparedness indicators increased significantly from pre‐ to posttest on both youth (p < 0.01) and parent ratings (p < 0.01). Parent ratings reflected an increase of just under six home‐based preparedness activities. Youth knowledge about disaster mitigation also was seen to increase significantly (p < 0.001), increasing 39% from pretest levels. While personalized risk perceptions significantly increased (p < 0.01), anxiety and worry levels were seen either not to change (generalized anxiety, p > 0.05) or to reduce between pre‐ and posttest (hazards‐specific fears, worry, and distress, ps ranged from p < 0.05 to < 0.001). In terms of predictors of preparedness, a number of variables were found to predict posttest preparedness levels, including information searching done by participants between education sessions. These pilot findings are the first to reflect quasi‐experimental outcomes for a youth hazards education program carried out in a setting other than a school that focused on a sample of youth from a low SES community.     

Replication: Revisiting Tversky and Shafir’s (1992) Disjunction Effect with an extension comparing between and within subject designs

Does uncertainty about an outcome influence decisions? The sure-thing principle (Savage, 1954) posits that it should not, but Tversky and Shafir (1992) found that people regularly violate it in hypothetical gambling and vacation decisions, a phenomenon they termed “disjunction effect”. Very close replications and extensions of Tversky and Shafir (1992) were conducted in this paper (N = 890, MTurk). The target article demonstrated the effect using two paradigms in a between-subject design: here, an extension also testing a within-subject design, with design being randomly assigned was added. These results were consistent with the original findings for the “paying to know“ problem (original: Cramer’s V = 0.22, 95% (CI) [0.14, 0.32]; replication: Cramer’s V = 0.30, 95% CI [0.24, 0.37]), yet not for the “choice under risk” problem (original: Cramer’s V = 0.26, 95% CI [0.14, 0.39]; replication: Cramer’s V = 0.11, 95% CI [−0.07, 0.20]). The within-subject extension showed very similar results. Implications for the disjunction effect and judgment and decision-making theory are discussed, and a call for improvements on the statistical understanding of comparisons of between-subject and within-subject designs is introduced. All materials, data, and code are available on https://osf.io/gu58m/.