Fewer but poorer: Benevolent partiality in prosocial preferences

A prosocial action typically provides a more sizable benefit when directed at those who have less as opposed to those who have more. However, not all prosocial acts have a direct bearing on socioeconomic disadvantage, nor does disadvantage necessarily imply a greater need for the prosocial outcome. Of interest here, welfare impact may depend on the number of beneficiaries but not on their socioeconomic status. Across four preregistered studies of life-saving decisions, we demonstrate that when allocating resources, many people are benevolently partial. That is, they choose to help the disadvantaged even when this transparently implies sacrificing lives. We suggest that people construct prosocial aid as an opportunity to correct morally aversive inequalities, thusmaking relativelymore disadvantaged recipients amore justifiable target of help. Benevolent partiality is reduced when people reflect beforehand on what aspects they will prioritize in their donation decision

Running experiments on Amazon Mechanical Turk

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool

Crowdsourced consumer data: how do we make sure it's good?

Crowdsourcing data through online marketplaces such as Amazon Mechanical Turk poses new challenges about how consumer research should be designed, conducted and analysed. Additionally, it raises questions about the validity of the participants and the information they provide. As protocols for crowdsourcing data are still being worked out, we have developed a few guidelines that will benefit those using such platforms for research purposes

Running experiments on Amazon Mechanical Turk

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool

Performance-based Earthquake Evaluation of a Full-Scale Petrochemical Piping System

Assessment of seismic vulnerability of industrial petrochemical and oil & gas piping systems can be performed, beyond analytical tools, through experimental testing as well. Along this line, this paper describes an experimental test campaign carried out on a full-scale piping system in order to assess its seismic behaviour. In particular, a typical industrial piping system, containing several critical components, such as elbows, a bolted flange joint and a Tee joint, was tested under different levels of realistic earthquake loading. They corresponded to serviceability and ultimate limit states for support structures as suggested by modern performance-based earthquake engineering standards. The so called hybrid simulation techniques namely, pseudo-dynamic and real time testing with dynamic substructuring, were adopted to perform seismic tests. Experimental results displayed a favorable performance of the piping system and its components; they remained below their yielding, allowable stress and allowable strain limits without any leakage even at the Near Collapse limit state condition for the support structure. Moreover, the favourable comparison between experimental and numerical results, proved the validity of the proposed hybrid techniques alternative to shaking table tests

Providing awareness, explanation and control of personalized filtering in a social networking site

Social networking sites (SNSs) have applied personalized filtering to deal with overwhelmingly irrelevant social data. However, due to the focus of accuracy, the personalized filtering often leads to “the filter bubble” problem where the users can only receive information that matches their pre-stated preferences but fail to be exposed to new topics. Moreover, these SNSs are black boxes, providing no transparency for the user about how the filtering mechanism decides what is to be shown in the activity stream. As a result, the user’s usage experience and trust in the system can decline. This paper presents an interactive method to visualize the personalized filtering in SNSs. The proposed visualization helps to create awareness, explanation, and control of personalized filtering to alleviate the “filter bubble” problem and increase the users’ trust in the system. Three user evaluations are presented. The results show that users have a good understanding about the filter bubble visualization, and the visualization can increase users’ awareness of the filter bubble, understandability of the filtering mechanism and to a feeling of control over the data stream they are seeing. The intuitiveness of the design is overall good, but a context sensitive help is also preferred. Moreover, the visualization can provide users with better usage experience and increase users’ trust in the system

An introduction to crowdsourcing for language and multimedia technology research

Language and multimedia technology research often relies on large manually constructed datasets for training or evaluation of algorithms and systems. Constructing these datasets is often expensive with significant challenges in terms of recruitment of personnel to carry out the work. Crowdsourcing methods using scalable pools of workers available on-demand offers a flexible means of rapid low-cost construction of many of these datasets to support existing research requirements and potentially promote new research initiatives that would otherwise not be possible

Hybrid simulations of a multi-span rc viaduct with plain bars and sliding bearings

This paper deals with the seismic response assessment of an old reinforced concrete viaduct and the effectiveness of friction-based retrofitting systems. Emphasis was laid on an old bridge, not properly designed to resist seismic action, consisting of 12 portal piers that support a 13-span bay deck for each independent roadway. On the basis of an OpenSEES finite element frame pier model, calibrated in a previous experimental campaign with cyclic displacement on three 1:4 scale frame piers, a more complex experimental activity using hybrid simulation has been devised. The aim of the simulation was twofold: (i) to increase knowledge of non-linear behavior of reinforced concrete frame piers with plain steel rebars and detailing dating from the late 1950s; and (ii) to study the effectiveness of sliding bearings for seismic response mitigation. Hence, to explore the performance of the as built bridge layout and also of the viaduct retrofitted with friction-based devices, at both serviceability and ultimate limit state conditions, hybrid simulation tests were carried out. In particular, two frame piers were experimentally controlled with eight-actuator channels in the as built case while two frame piers and eight sliding bearings were controlled with 18-actuator channels in the isolated case. The remaining frame piers were part of numerical substructures and were updated offline to accurately track damage evolution