Eleventh annual report of the Society for the Diffusion of Christian & General Knowledge among the Chinese, for the year ending 31st October, 1898

In volume lettered: Pamphlets on China, 23

Approaches to the Study of English Forename Use

Peer reviewedFinal Published versio

Political, religious and occupational identities in context: Placing identity status paradigm in context

This study critically contrasts global identity with domain-specific identities (political, religious and occupational) and considers context and gender as integral parts of identity. In a cross-sectional survey, 1038 Greek Cypriot adolescents (449 boys and 589 girls, mean age 16.8) from the three different types of secondary schools (state, state technical and private) and from different SES completed part of the Extended Objective Measure of Ego-Identity Status-2 (EOMEIS-2). The macrocontext of Greek Cypriot society is used to understand the role of context in adolescents’ identities. Results showed that Greek Cypriot young people were not in the same statuses across their global, political, religious and occupational identities. This heterogeneity in the status of global identity and of each identity domain is partially explained by differences in gender, type of school and SES (Socio-Economic Status). The fact that identity status is found to be reactive to context suggests that developmental stage models of identity status should place greater emphasis on context

Construction of embedded fMRI resting state functional connectivity networks using manifold learning

We construct embedded functional connectivity networks (FCN) from benchmark resting-state functional magnetic resonance imaging (rsfMRI) data acquired from patients with schizophrenia and healthy controls based on linear and nonlinear manifold learning algorithms, namely, Multidimensional Scaling (MDS), Isometric Feature Mapping (ISOMAP) and Diffusion Maps. Furthermore, based on key global graph-theoretical properties of the embedded FCN, we compare their classification potential using machine learning techniques. We also assess the performance of two metrics that are widely used for the construction of FCN from fMRI, namely the Euclidean distance and the lagged cross-correlation metric. We show that the FCN constructed with Diffusion Maps and the lagged cross-correlation metric outperform the other combinations

Modeling the adoption and use of social media by nonprofit organizations

This study examines what drives organizational adoption and use of social media through a model built around four key factors - strategy, capacity, governance, and environment. Using Twitter, Facebook, and other data on 100 large US nonprofit organizations, the model is employed to examine the determinants of three key facets of social media utilization: 1) adoption, 2) frequency of use, and 3) dialogue. We find that organizational strategies, capacities, governance features, and external pressures all play a part in these social media adoption and utilization outcomes. Through its integrated, multi-disciplinary theoretical perspective, this study thus helps foster understanding of which types of organizations are able and willing to adopt and juggle multiple social media accounts, to use those accounts to communicate more frequently with their external publics, and to build relationships with those publics through the sending of dialogic messages.Comment: Seungahn Nah and Gregory D. Saxton. (in press). Modeling the adoption and use of social media by nonprofit organizations. New Media & Society, forthcomin

Pioneering marriage for same-sex couples in the Netherlands

Why did the Netherlands become the first country to allow same-sex couples to marry? I argue that in addition to social and political factors that have been well-highlighted in the literature, the desire of Dutch activists and policy élites to burnish their international reputation as a social policy and lesbian, gay, bisexual and transgender rights pioneer played a critical role in motivating the government to adopt this controversial policy. In making this argument, the article addresses the often neglected topic of policy invention. I utilize the concept of regional policy community drawn from federalism studies to illustrate that such communities do not just facilitate the diffusion of new innovations across its constituent states, but they can also inspire pioneering states to experiment with new policy models in the first place

The Muslim colony of Luceria Sarracenorum (Lucera) : life and dispersion as outlined by onomastic evidence

The life and dispersion of Lucerine Muslims in Apulia (c.1220-1300) are examined from the onomastic point of view. Many Muslim names are recorded in Latin scripted official documents. These do not differ greatly from those reported by Salvatore Cusa and those found in the Maltese Militia List of 1419/20. Some Lucerine names present several variants which can be used as 'markers' to locate the presence of Muslims after their dispersion. The diffusion of modern surnames related to these markers confirms reports in Angevin documents, namely that the cities of Naples and Barletta were the main centres for the subsequent relocation of Muslims. However, large concentrations of these surnames are to be found also in the regions of Latium and the Marches.peer-reviewe

Towards an Efficient Finite Element Method for the Integral Fractional Laplacian on Polygonal Domains

We explore the connection between fractional order partial differential equations in two or more spatial dimensions with boundary integral operators to develop techniques that enable one to efficiently tackle the integral fractional Laplacian. In particular, we develop techniques for the treatment of the dense stiffness matrix including the computation of the entries, the efficient assembly and storage of a sparse approximation and the efficient solution of the resulting equations. The main idea consists of generalising proven techniques for the treatment of boundary integral equations to general fractional orders. Importantly, the approximation does not make any strong assumptions on the shape of the underlying domain and does not rely on any special structure of the matrix that could be exploited by fast transforms. We demonstrate the flexibility and performance of this approach in a couple of two-dimensional numerical examples

Eliminating unpredictable variation through iterated learning

Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might result from a process of iterated learning in simple diffusion chains of adults. An iterated artificial language learning methodology was used, in which participants were organised into diffusion chains: the first individual in each chain was exposed to an artificial language which exhibited unpredictability in plural marking, and subsequent learners were exposed to the language produced by the previous learner in their chain. Diffusion chains, but not isolate learners, were found to cumulatively increase predictability of plural marking by lexicalising the choice of plural marker. This suggests that such gradual, cumulative population-level processes offer a possible explanation for regularity in language

Bayesian Item Response Modeling in R with brms and Stan

Item Response Theory (IRT) is widely applied in the human sciences to model persons' responses on a set of items measuring one or more latent constructs. While several R packages have been developed that implement IRT models, they tend to be restricted to respective prespecified classes of models. Further, most implementations are frequentist while the availability of Bayesian methods remains comparably limited. We demonstrate how to use the R package brms together with the probabilistic programming language Stan to specify and fit a wide range of Bayesian IRT models using flexible and intuitive multilevel formula syntax. Further, item and person parameters can be related in both a linear or non-linear manner. Various distributions for categorical, ordinal, and continuous responses are supported. Users may even define their own custom response distribution for use in the presented framework. Common IRT model classes that can be specified natively in the presented framework include 1PL and 2PL logistic models optionally also containing guessing parameters, graded response and partial credit ordinal models, as well as drift diffusion models of response times coupled with binary decisions. Posterior distributions of item and person parameters can be conveniently extracted and post-processed. Model fit can be evaluated and compared using Bayes factors and efficient cross-validation procedures.Comment: 54 pages, 16 figures, 3 table