Social acceleration and the network effect: a defence of social ‘science fiction’ and network determinism

This essay is a response to Judy Wajcman's essay ‘Life in the fast lane? Towards a sociology of technology and time’ (2008: 59–77). In that article Wajcman argued that recent developments in the sociology of temporal change had been marked by a tendency in social theory towards a form of ‘science fiction’– a sociological theorizing, she maintains, that bears no real relation to actual, empirically provable developments in the field and should therefore be viewed as not contributing to ‘a richer analysis of the relationship between technology and time’ (2008: 61). This reply argues that as Wajcman suggests in her essay, there is indeed an ‘urgent need for increased dialogue to connect social theory with detailed empirical studies’ (2008: 59) but that the most fruitful way to proceed would not be through a constraining of ‘science fiction’ social theorizing but, rather, through its expansion – and more, that ‘science fiction’ should take the lead in the process. This essay suggests that the connection between social theory and empirical studies would be strengthened by a wider understanding of the function of knowledge and research in the context of what is termed ‘true originality’ and ‘routine originality’. The former is the domain of social theory and the latter resides within traditional sociological disciplines. It is argued that both need each other to advance our understanding of society, especially in the context of the fast‐changing processes of technological development. The example of ‘technological determinism’ is discussed as illustrative of how ‘routine originality’ can harden into dogma without the application of ‘true originality’ to continually question (sometimes through ideas that may appear to border on ‘science fiction’) comfortable assumptions that may have become ‘routine’ and shorn of their initial ‘originality’.     

Screening for recommended antenatal risk factors: How long does it take?

Background

Detection and management of antenatal risk factors is critical for quality care.

Household and Contextual Indicators of Poverty in Tunisia: A Multilevel Analysis

Using micro data from the 2010 National Survey on Households’ Budget, Consumption and Standard of Living, this study aims to investigate main factors contributing to poverty distribution, one of the most severe socioeconomic problems in Tunisia. To this end, we use a multilevel Logit model and a multilevel mixed linear model to simultaneously analyze the micro-level (household) and macro-level (governorate) factors that might affect the household poverty status. Household size, household composition, occupation, education levels, the gender of the household head and the number of earner by household variables were assessed at the micro-level. Unemployment rate, poverty rate, industrial and agriculture parts and the migration are included to control the effect of contextual effects. Our findings showed that the likelihood of household being poor is positively and significantly related to household size, more children and lower education level. Extreme poverty is more likely to occur in rural than urban areas. Macro-level analyses indicated that greater neighbourhood unemployment rate was associated with higher odds of poverty, while greater industrial agglomeration and migration balance were associated with reduced odds of poverty.     

Terrorism and the integration of Muslim immigrants

We study the effect that a series of Islamist terrorist attacks across Europe in 2004–2005 had on the integration of Muslim immigrants. Using unique panel data that oversamples immigrants in the Netherlands, we show that, shortly after the attacks, Muslim immigrants’ attitudes toward integration worsened significantly compared to those of non-Muslim immigrants, with no evidence of a negative trend in the attitudes of Muslims prior to the attacks. While, in particular, low-educated Muslims became more geographically segregated and unemployed after the attacks, high-educated Muslims were affected most negatively in terms of their perceived integration. This decline in perceived integration is associated with a higher intention to permanently re-migrate to the country of origin.     

Estimation of generalized exponential distribution based on an adaptive progressively type-II censored sample

In this paper, based on an adaptive Type-II progressively censored sample from the generalized exponential distribution, the maximum likelihood and Bayesian estimators are derived for the unknown parameters as well as the reliability and hazard functions. Also, the approximate confidence intervals of the unknown parameters, and the reliability and hazard functions are calculated. Markov chain Monte Carlo method is applied to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. Moreover, results from simulation studies assessing the performance of our proposed method are included. Finally, an illustrative example using real data set is presented for illustrating all the inferential procedures developed here.     

Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies

The aim of this work is to study in a first step the dependence between oil and some commodity prices (cotton, rice, wheat, sucre, coffee, and silver) using copula theory, and then in a second step to determine the optimal hedging strategy for oil–commodity portfolio against the risk of negative variation in commodity markets prices. The model is implemented with an AR-GARCH model with innovations that follow t distribution for the marginal distribution and the extreme value copula for the joint distribution and parameters and dependence indices are re-estimated in each new day which allow taking into account nonlinear dependence, tails behavior, and their development over time. Various copula functions are used to model the dependence structure between oil and commodity markets. Empirical results show an increase in the dependence during the last 6 years. Volatility for commodity prices registered record levels in the same time with the increase in uncertainty. Optimal hedging ratio varies over time as a consequence of the change in the dependence structure.     

A generalized binomial exponential 2 distribution: modeling and applications to hydrologic events

Developing statistical methods to model hydrologic events is always interesting for both statisticians and hydrologists, because of its importance in hydraulic structures design and water resource planning. Because of this, a flexible 3-parameter generalization of the exponential distribution is introduced based on the binomial exponential 2 (BE2) distribution [2 H.S. Bakouch, M. Aghababaei Jazi, S. Nadarajah, A. Dolati, and R. Roozegar, A lifetime model with increasing failure rate, Appl. Math. Model. 38 (2014), pp. 5392–5406. doi: 10.1016/j.apm.2014.04.028[Crossref], [Web of Science ®] , [Google Scholar]]. The proposed distribution involving the exponential, gamma and BE2 distributions as submodels; and it exhibits decreasing, increasing and bathtub-shaped hazard rates, so it turns out to be quite flexible for analyzing non-negative real life data. Some statistical properties, parameters estimation and information matrix of the distribution are investigated. The proposed distribution, Gumbel, generalized Logistic and other distributions are utilized to model and fit two hydrologic data sets. The distribution is shown to be more appropriate to the data than the compared distributions using the selection criteria: average scaled absolute error, Akaike information criterion, Bayesian information criterion and Kolmogorov–Smirnov statistics. As a result, some hydrologic parameters of the data are obtained such as return level, conditional mean, mean deviation about the return level and the rth moments of order statistics.     

New confidence interval estimator of the signal-to-noise ratio based on asymptotic sampling distribution

In this paper, the asymptotic distribution of the signal-to-noise ratio (SNR) is derived and a new confidence interval for the SNR is introduced. An evaluation of the performance of the new interval compared to Sharma and Krishna (S–K) (1994) confidence interval for the SNR using Monte Carlo simulations is conducted. Data were randomly generated from normal, log-normal, χ², Gamma, and Weibull distributions. Simulations revealed that the performance of S–K interval is totally dependent on the amount of noise introduced and that it has a constant width for a given sample size. The S–K interval performs poorly in four of the distributions unless the SNR is around one. It is recommended against using the S–K interval for data from log-normal distribution even with SNR = 1. Unlike the S–K interval which does not account for skewness and kurtosis of the distribution, the new confidence interval for the SNR outperforms S–K for all five distributions discussed, especially when SNR?? 2. The proposed ranked set sampling (RSS) instead of simple random sampling (SRS) has improved the performance of both intervals as measured by coverage probability.     

On the b-coloring of tight graphs

A coloring c of a graph \(G=(V,E)\) is a b -coloring if for every color i there is a vertex, say w(i), of color i whose neighborhood intersects every other color class. The vertex w(i) is called a b-dominating vertex of color i. The b -chromatic number of a graph G, denoted by b(G), is the largest integer k such that G admits a b-coloring with k colors. Let m(G) be the largest integer m such that G has at least m vertices of degree at least \(m-1\). A graph G is tight if it has exactly m(G) vertices of degree \(m(G)-1\), and any other vertex has degree at most \(m(G)-2\). In this paper, we show that the b-chromatic number of tight graphs with girth at least 8 is at least \(m(G)-1\) and characterize the graphs G such that \(b(G)=m(G)\). Lin and Chang (2013) conjectured that the b-chromatic number of any graph in \(\mathcal {B}_{m}\) is m or \(m-1\) where \(\mathcal {B}_{m}\) is the class of tight bipartite graphs \((D,D{^\prime })\) of girth 6 such that D is the set of vertices of degree \(m-1\). We verify the conjecture of Lin and Chang for some subclass of \(\mathcal {B}_{m}\), and we give a lower bound for any graph in \(\mathcal {B}_{m}\).     

The Role of Religiosity on the Relationship Between Materialism and Fashion Clothing Consumption Among Malaysian Generation Y Consumers

Religiosity is a significant cultural force influencing various dimensions of consumer behaviours; however, its role in the literature on fashion clothing remains unclear. To rectify this paucity of information, this study explores the relationship between religiosity, materialism and fashion clothing involvement (FCI); and religiosity, materialism and fashion clothing purchase involvement (FCPI). Using a sample of 282 Malaysian Generation Y consumers, it employs a positivist research approach, comprising of a quantitative basis of enquiry, and gathered data via survey questionnaires. The research findings show that religiosity moderates the relationship between materialism and FCI, as well as materialism and FCPI, where an individual’s religiosity is inversely associated with FCPI. Another finding is the importance of FCI in mediating the relationship between materialism and FCPI, plus the significance of mediated moderation and its effects on the relationship between materialism and FCPI. The findings reinforce the role of religiosity in consumer involvement in fashion clothing and fashion clothing purchase trends. Recognition of this significant construct and its importance may enable marketers to develop more sophisticated positioning strategies.