Social Simulation That 'Peers into Peer Review'

This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved.Peer Review, Social Simulation, Social Norms, Selection Biases, Science Policy

Social Simulation That 'Peers into Peer Review'

This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved

Increasing Confidence of Nurses in Giving and Receiving Constructive Performance Feedback

Background: Nursing peer review is a process of reviewing standard nursing practice in an organization and comparing a nurse’s own practice to that standard. Nursing peer review contributes to the professional practice environment by assuring standard practice and competence, maintaining a culture of accountability, and maintaining psychological safety. Purpose: The purpose of this project was to design and implement an educational intervention and simulation activity to prepare nurses to have constructive conversations with peers regarding work performance. Evaluation of the intervention would yield increased confidence and competence of nursing staff in giving constructive performance peer feedback. Conceptual Framework: Bandura’s Social Cognitive Theory informed this study, supporting that adopting new behaviors will allow participants to feel they have control over the needed change. As new behaviors are incorporated into practice, they become habitual and contribute to the practice environment. Methods: In this quasi-experimental study, a sample (n=16) of nurses in the medicine service line of a hospital in an academic healthcare system participated in an educational session and a simulation activity to provide them with the knowledge to confidently participate in performance feedback conversations with peers. Results: Data indicate that the education session and simulation activity did improve confidence of nurses in giving constructive feedback to their peers. Feelings of apprehension in giving peer feedback did decrease, though not to a statistically significant level (p = 0.07). Discussion: Education and practice in this skill result in decreased apprehension in giving feedback and increase confidence of nurses in giving peer feedback. Participants learned to give honest and meaningful information in a timely fashion. Strong communication skills are essential to both patient care and working with the care team. Poor delivery of feedback will damage trust, but will be motivational and goal-directed when done correctly. Conclusion: In order for meaningful feedback to be shared, nursing staff need to be adequately educated and prepared. Effective communication is essential to building a strong team and creating a psychologically safe practice environment

The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results

Group behavior impact on an opportunistic localization scheme

In this paper we tackled the localization problem from an opportunistic perspective, according to which a node can infer its own spatial position by exchanging data with passing by nodes, called peers. We consider an opportunistic localization algorithm based on the linear matrix inequality (LMI) method coupled with a weighted barycenter algorithm. This scheme has been previously analyzed in scenarios with random deployment of peers, proving its effectiveness. In this paper, we extend the analysis by considering more realistic mobility models for peer nodes. More specifically, we consider two mobility models, namely the Group Random Waypoint Mobility Model and the Group Random Pedestrian Mobility Model, which is an improvement of the first one. Hence, we analyze by simulation the opportunistic localization algorithm for both the models, in order to gain insights on the impact of nodes mobility pattern onto the localization performance. The simulation results show that the mobility model has non-negligible effect on the final localization error, though the performance of the opportunistic localization scheme remains acceptable in all the considered scenarios

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the pattern by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game makes a decision among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information

Household debt and social interactions : [Version 1 März 2012]

Debt-induced crises, including the subprime, are usually attributed exclusively to supply-side factors. We examine the role of social influences on debt culture, emanating from perceived average income of peers. Utilizing unique information from a household survey representative of the Dutch population, that circumvents the issue of defining the social circle, we consider collateralized, consumer, and informal loans. We find robust social effects on borrowing, especially among those who consider themselves poorer than their peers; and on indebtedness, suggesting a link to financial distress. We employ a number of approaches to rule out spurious associations and to handle correlated effects