The Use of Internet Chat Rooms to Meet Sexual Partners: A Comparison of Non-Heterosexually Identified Men with Heterosexually Identified Men and Women

ABSTRACT. Objectives: Prior work suggests that many individuals use the Internet to meet romantic or sexual partners. Our intent was to explore perceptions and experiences with meeting people online. Methods: In 2008, the authors conducted U.S.-based online interviews with 65 predominantly White, self-identified heterosexual men and women and gay/bisexual men (Mean age = 30.8 years). Results: Reasons for meeting people online, desired partner characteristics, and the process of connecting for sex paralleled those observed in face-to-face contexts. People used Internet chat rooms to identify more partners and specific partner characteristics. “Background checks” of online partners, though often believed to be inaccurate, increased familiarity and trust leading to reduced condom use. Participants said online condom use negotiation was easier but usually occurred in face-to-face contexts. Conclusions: The fundamental processes of meeting partners online are similar in many ways to meeting partners face-to-face; however, the Internet facilitates rapid access to relatively large numbers of potential partners.     

Uniform Ergodicity of the Particle Gibbs Sampler

The particle Gibbs sampler is a systematic way of using a particle filter within Markov chain Monte Carlo. This results in an off‐the‐shelf Markov kernel on the space of state trajectories, which can be used to simulate from the full joint smoothing distribution for a state space model in a Markov chain Monte Carlo scheme. We show that the particle Gibbs Markov kernel is uniformly ergodic under rather general assumptions, which we will carefully review and discuss. In particular, we provide an explicit rate of convergence, which reveals that (i) for fixed number of data points, the convergence rate can be made arbitrarily good by increasing the number of particles and (ii) under general mixing assumptions, the convergence rate can be kept constant by increasing the number of particles superlinearly with the number of observations. We illustrate the applicability of our result by studying in detail a common stochastic volatility model with a non‐compact state space.     

I agreed to go because........examining the Agency of Children within a phenomenon conceptualised as trafficking in Ghana

The legal and policy framework on child trafficking is dismissive of children's agency and regards them as vulnerable personalities. This paper examines the scope of children's agency in their transportation to other communities for fishing in Ghana. Using a phenomenological design, 17 child returnees' views were elicited on their movement for fishing activities. Findings revealed that children's agentive capabilities progressed primarily from consent giving to negotiation. Highlighting the relational and material context within which children's agency unfolds, the study suggests that it is erroneous to generally ascribe the discursive label of ‘innocence’ to children who are considered as trafficked.     

Fiscal Foresight and Information Flows

News—or foresight—about future economic fundamentals can create rational expectations equilibria with non‐fundamental representations that pose substantial challenges to econometric efforts to recover the structural shocks to which economic agents react. Using tax policies as a leading example of foresight, simple theory makes transparent the economic behavior and information structures that generate non‐fundamental equilibria. Econometric analyses that fail to model foresight will obtain biased estimates of output multipliers for taxes; biases are quantitatively important when two canonical theoretical models are taken as data generating processes. Both the nature of equilibria and the inferences about the effects of anticipated tax changes hinge critically on hypothesized information flows. Different methods for extracting or hypothesizing the information flows are discussed and shown to be alternative techniques for resolving a non‐uniqueness problem endemic to moving average representations.     

Marketing Is from Mars,IT Is from Venus: Aligning the Worldviews for Firm Performance

A typical firm is operated by multiple functional managers who may collaborate as well as compete to achieve firm performance. In the digital age, firm performance is essentially customer‐dependent and technology‐dependent, with both marketing and information technology (IT) playing key roles. Unfortunately the two functions often have very different worldviews. We show how these differences can damage firm performance, and suggest ways to mitigate this damage. We build a worldview difference model, synthesized from multiple disciplines. The model is tested using both matched and nonmatched observations from marketing and IT managers, and is analyzed with hierarchical linear models using both perceptual and objective firm performance data over a 4‐year period. We find that differences between the beliefs and perceptions of marketing managers and IT managers generate a negative impact on firm performance, and suggest appropriate technology‐culture associations to effectively align their worldviews for firm performance. To improve firm performance, a cross‐functional appreciation for market and technology drivers can be achieved by making marketing managers more learning‐oriented and by providing IT managers a culture that is congruent with technology.     

Cross-country risk quantification of extreme wildfires in Mediterranean Europe

We estimate the country-level risk of extreme wildfires defined by burned area (BA) for Mediterranean Europe and carry out a cross-country comparison. To this end, we avail of the European Forest Fire Information System (EFFIS) geospatial data from 2006 to 2019 to perform an extreme value analysis. More specifically, we apply a point process characterization of wildfire extremes using maximum likelihood estimation. By modeling covariates, we also evaluate potential trends and correlations with commonly known factors that drive or affect wildfire occurrence, such as the Fire Weather Index as a proxy for meteorological conditions, population density, land cover type, and seasonality. We find that the highest risk of extreme wildfires is in Portugal (PT), followed by Greece (GR), Spain (ES), and Italy (IT) with a 10-year BA return level of 50'338 ha, 33'242 ha, 25'165 ha, and 8'966 ha, respectively. Coupling our results with existing estimates of the monetary impact of large wildfires suggests expected losses of 162–439 million € (PT), 81–219 million € (ES), 41–290 million € (GR), and 18–78 million € (IT) for such 10-year return period events.

SUMMARY

We model the risk of extreme wildfires for Italy, Greece, Portugal, and Spain in form of burned area return levels, compare them, and estimate expected losses.     

How to Code a Million Missions: Developing Bespoke Nonprofit Activity Codes Using Machine Learning Algorithms

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - National Taxonomy of Exempt Entities (NTEE) codes have become the primary classifier of nonprofit missions since they were...