58 research outputs found
Statistics of statisticians: Critical mass of statistics and operational research groups in the UK
Using a recently developed model, inspired by mean field theory in
statistical physics, and data from the UK's Research Assessment Exercise, we
analyse the relationship between the quality of statistics and operational
research groups and the quantity researchers in them. Similar to other academic
disciplines, we provide evidence for a linear dependency of quality on quantity
up to an upper critical mass, which is interpreted as the average maximum
number of colleagues with whom a researcher can communicate meaningfully within
a research group. The model also predicts a lower critical mass, which research
groups should strive to achieve to avoid extinction. For statistics and
operational research, the lower critical mass is estimated to be 9 3. The
upper critical mass, beyond which research quality does not significantly
depend on group size, is about twice this value
Academic research groups: evaluation of their quality and quality of their evaluation
In recent years, evaluation of the quality of academic research has become an
increasingly important and influential business. It determines, often to a
large extent, the amount of research funding flowing into universities and
similar institutes from governmental agencies and it impacts upon academic
careers. Policy makers are becoming increasingly reliant upon, and influenced
by, the outcomes of such evaluations. In response, university managers are
increasingly attracted to simple indicators as guides to the dynamics of the
positions of their various institutions in league tables. However, these league
tables are frequently drawn up by inexpert bodies such as newspapers and
magazines, using rather arbitrary measures and criteria. Terms such as
"critical mass' and "metrics" are often bandied about without proper
understanding of what they actually mean. Rather than accepting the rise and
fall of universities, departments and individuals on a turbulent sea of
arbitrary measures, we suggest it is incumbent upon the scientific community
itself to clarify their nature. Here we report on recent attempts to do that by
properly defining critical mass and showing how group size influences research
quality. We also examine currently predominant metrics and show that these fail
as reliable indicators of group research quality.Comment: Presented at the International Conference on Computer Simulation in
Physics and Beyond in Moscow, 2015. The Proceedings will appear in Journal of
Physics: Conference Series (JPCS
Sleep deprivation impairs and caffeine enhances my performance, but not always our performance: how acting in a group can change the effects of impairments and enhancements
What effects do factors that impair or enhance performance in individuals have when these individuals act in groups? We provide a framework, called the GIE ("Effects of Grouping on Impairments and Enhancements”) framework, for investigating this question. As prominent examples for individual-level impairments and enhancements, we discuss sleep deprivation and caffeine. Based on previous research, we derive hypotheses on how they influence performance in groups, specifically process gains and losses in motivation, individual capability, and coordination. We conclude that the effect an impairment or enhancement has on individual-level performance is not necessarily mirrored in group performance: grouping can help or hurt. We provide recommendations on how to estimate empirically the effects individual-level performance impairments and enhancements have in groups. By comparing sleep deprivation to stress and caffeine to pharmacological cognitive enhancement, we illustrate that we cannot readily generalize from group results on one impairment or enhancement to another, even if they have similar effects on individual-level performance
Nash Equilibria in Multi-Agent Motor Interactions
Social interactions in classic cognitive games like the ultimatum game or the
prisoner's dilemma typically lead to Nash equilibria when multiple
competitive decision makers with perfect knowledge select optimal strategies.
However, in evolutionary game theory it has been shown that Nash equilibria can
also arise as attractors in dynamical systems that can describe, for example,
the population dynamics of microorganisms. Similar to such evolutionary
dynamics, we find that Nash equilibria arise naturally in motor interactions in
which players vie for control and try to minimize effort. When confronted with
sensorimotor interaction tasks that correspond to the classical
prisoner's dilemma and the rope-pulling game, two-player motor
interactions led predominantly to Nash solutions. In contrast, when a single
player took both roles, playing the sensorimotor game bimanually, cooperative
solutions were found. Our methodology opens up a new avenue for the study of
human motor interactions within a game theoretic framework, suggesting that the
coupling of motor systems can lead to game theoretic solutions
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