The Solidary Relationship’s Consequences for the Ebb and Flow of Activism: Collaborative Evidence from Life-History Interviews and Social Media Event Analysis,

Acting in solidarity with deprived others has become a central topic in social movement research. The explanations of solidarity activism or political altruism are few. However, social movement researchers have claimed that solidarity with out-of-group others is a by-product of in-group interaction. In contrast, we argue that out-group interaction with the deprived other and the formation of a solidary relationship is central to the ebb and flow of solidarity activism. We investigate the Danish refugee solidarity movement and show that the meeting with the deprived other 1) brings about an interaction order which makes an ethical demand on the activists to care for the other both within the bounds of the situations and in the future; 2) enacts and amplifies activists’ values and beliefs because the deprived other becomes an exemplar of the injustice and the need to help the broader group of people in the same fragile situation. We develop and test this theory drawing on 42 life-history interviews and a social media dataset containing a panel of 87,455 activists participating in refugee solidarity groups.     

Professionalization through attrition? An event history analysis of mortalities in citizen journalism

ABSTRACT

Despite both scholarly and popular claims that citizen journalism (CJ) represents a growing democratizing force in the journalistic field, recent scholarship in the area has noted the decline of the organizational population of CJ. In this paper, we investigate how individual characteristics of sites and the dynamics of larger organizational population affect a CJ site’s risk of experiencing a mortality. Drawing on the largest sample to date of US-based English-language CJ sites, this study examines the risk of site mortality through an event history framework. Findings indicate that the strongest predictor of a site’s mortality is the age of the site, consistent with organizational population theory’s ‘liability of newness.’ We also find that for-profit and community-based sites have lower rates of site mortality, indicating that adopting legitimate conventions of journalism may serve as a protective buffer to site death. The results offer mixed evidence on whether CJ has become more professionalized via attrition.     

Max‐infinitely divisible models and inference for spatial extremes

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max‐stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max‐infinitely divisible processes, which extend max‐stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max‐infinitely divisible models, which relax the max‐stability property but remain close to some popular max‐stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max‐stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student‐t copula process and its max‐stable limit, even for large block sizes.     

Principal stratum strategy: Potential role in drug development

A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristics. Often, however, clinical questions also arise regarding the treatment effect in subpopulations of patients, which would experience clinical or disease related events post-randomization. Events that occur after treatment initiation and potentially affect the interpretation or the existence of the measurements are called intercurrent events in the ICH E9(R1) guideline. If the intercurrent event is a consequence of treatment, randomization alone is no longer sufficient to meaningfully estimate the treatment effect. Analyses comparing the subgroups of patients without the intercurrent events for intervention and control will not estimate a causal effect. This is well known, but post-hoc analyses of this kind are commonly performed in drug development. An alternative approach is the principal stratum strategy, which classifies subjects according to their potential occurrence of an intercurrent event on both study arms. We illustrate with examples that questions formulated through principal strata occur naturally in drug development and argue that approaching these questions with the ICH E9(R1) estimand framework has the potential to lead to more transparent assumptions as well as more adequate analyses and conclusions. In addition, we provide an overview of assumptions required for estimation of effects in principal strata. Most of these assumptions are unverifiable and should hence be based on solid scientific understanding. Sensitivity analyses are needed to assess robustness of conclusions.     

Modelling period fertility: Schooling and intervals following a birth in Eastern Africa

We describe a regression-based approach to the modelling of age-, order-, and duration-specific period fertility, using retrospective survey data. The approach produces results that are free of selection biases and can be used to study differential fertility. It is applied to Demographic and Health Survey data for Ethiopia, Kenya, Tanzania, and Zimbabwe to investigate differential trends in fertility by education. Parity progression fell and the intervals following each birth lengthened between the 1970s and 2000s in all four countries. Fertility fell most among women with secondary education. In contrast to other world regions, postponement of successive births for extended periods accounted for much of the initial drop in fertility in these African countries. However, family size limitation by women with secondary education in Ethiopia and Kenya and longer birth spacing in Zimbabwe also played significant roles. Thus, birth control is being adopted in Eastern Africa in response to diverse changes in fertility preferences.     

Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

Marriage and separation risks among German cohabiters: Differences between types of cohabiter

We propose a typology of different meanings of cohabitation that combines cohabiters’ intentions to marry with a general attitude toward marriage, using competing risk analyses to examine whether some cohabiters are more prone than others to marry or to separate. Using data (N = 1,258) from four waves of the German Family Panel (PAIRFAM) and a supplementary study (DEMODIFF), we compared eastern and western German cohabiters of the birth cohorts 1971–73 and 1981–83. Western Germans more frequently view cohabitation as a step in the marriage process, whereas eastern Germans more often cohabit as an alternative to marriage. Taking into account marital attitudes reveals that cohabiters without marriage plans differ from those with plans in their relationship careers, and also shows that cohabiters who plan to marry despite holding a less favourable view of marriage are less likely to realize their plans than cohabiters whose intentions and attitudes are more congruent.     

A class of additive transformation models for recurrent gap times

Abstract

The gap time between recurrent events is often of primary interest in many fields such as medical studies, and in this article, we discuss regression analysis of the gap times arising from a general class of additive transformation models. For the problem, we propose two estimation procedures, the modified within-cluster resampling (MWCR) method and the weighted risk-set (WRS) method, and the proposed estimators are shown to be consistent and asymptotically follow the normal distribution. In particular, the estimators have closed forms and can be easily determined, and the methods have the advantage of leaving the correlation among gap times arbitrary. A simulation study is conducted for assessing the finite sample performance of the presented methods and suggests that they work well in practical situations. Also the methods are applied to a set of real data from a chronic granulomatous disease (CGD) clinical trial.     

中国诗学中的事境说

事境是中国诗学独创的一个概念,但一直被抒情传统的意境说所遮蔽。事境说是宋代以来世俗化生活在诗学领域的一种反映。与“想味不尽”的意境不同,事境尚实宜近,是时间(事)空间化(境)审美范畴。从诗性生存的角度看,诗人创设事境就是为了使人摆脱日常之事的纷扰,在事的诗性世界里去感受和体验应然的生活,从而使人心灵得以净化,生活得以提升。深入发掘和研究事境,既有助于全面理解中国诗学的历史传统,也有助于当下诗歌与诗学多元鉴赏与建设。     

A seasonal mixed-POT model to estimate high flood quantiles from different event types and seasons

Flood events can be caused by several different meteorological circumstances. For example, heavy rain events often lead to short flood events with high peaks, whereas snowmelt normally results in events of very long duration with a high volume. Both event types have to be considered in the design of flood protection systems. Unfortunately, all these different event types are often included in annual maximum series (AMS) leading to inhomogeneous samples. Moreover, certain event types are underrepresented in the AMS. This is especially unsatisfactory if the most extreme events result from such an event type. Therefore, monthly maximum data are used to enlarge the information spectrum on the different event types. Of course, not all events can be included in the flood statistics because not every monthly maximum can be declared as a flood. To take this into account, a mixture Peak-over-threshold model is applied, with thresholds specifying flood events of several types that occur in a season of the year. This model is then extended to cover the seasonal type of the data. The applicability is shown in a German case study, where the impact of the single event types in different parts of a year is evaluated.