National service: the sixties meet the nineties

City Year is a community service program in Boston, MA, envisioned to help empower citizens to solve their own problems in the area. The program\u27s citizen participation component reincarnates an ideology upheld by the youth in the 1960s

Collective Bargaining, Mutuality, and Workers Participation in Management: An International Analysis

Les efforts entrepris pour développer la participation des travailleurs à la gestion ont principalement suivi deux voies. L'une, dont la négociation collective est un exemple, implique l'antagonisme; l'autre, représentée par les groupes de travail autonomes, la coopération des producteurs et (dans certaines limites) la cogestion, est de nature mutualiste ou consensuelle. Aux États-Unis et en Grande-Bretagne, c'est le modèle antagoniste que l'on trouve généralement dans les usines et les industries où les salariés sont syndiqués. Dans le système d'autogestion de la Yougoslavie, les kibboutz d'Israël et les coopératives de producteurs d'un certain nombre de pays, c'est le modèle mutualiste qui a été adopté. Mais on a aussi, en République fédérale d'Allemagne, en Suède et au Japon, des exemples de systèmes où les deux méthodes existent côte à côte dans la même industrie ou la même entreprise. Et il existe certaines manières de procéder qui combinent les conceptions antagoniques et mutualistes.Bien que le système de négociation collective des États-Unis soit fondé sur l'antagonisme, certains employeurs et syndicats ont évolué vers la méthode mutualiste en créant des commissions ou des programmes mixtes de coopération, dont les tâches sont ordinairement bien déterminées. Les résultats de la coopération dans le domaine du rendement de la production, de la réduction des coûts et de la lutte contre le gaspillage ont été minces. Dans la plupart des cas, les expériences faites aux États-Unis en matière d'enrichissement et de valorisation des tâches ainsi qu'avec les groupes de travail semi-autonomes ont eu lieu dans des établissements dont le personnel n'était pas syndiqué. La méthode antagoniste permet théoriquement de régler à peu près tous les problèmes et questions relevant de la méthode mutualiste, mais les syndicats américains se sont bornés à diriger leurs efforts vers l'organisation rigoureuse et la réglementation des questions d'emploi.L'expérience de la République fédérale d'Allemagne, de la Suède et de quelques autres pays d'Europe montre bien que le champ de la négociation collective peut s'étendre au-delà des questions classiques de salaires et de conditions d'emploi et être, en même temps, lié à des programmes mutualistes au lieu de travail et au conseil de direction. Les objectifs et les attitudes jouent un rôle capital dans ces cas. Il est significatif que le mutualisme soit souvent le résultat de l'action du pouvoir politique ou d'une redistribution de ce pouvoir dans l'ensemble de la société. Mais la volonté a aussi contribué dans une mesure capitale à donner leur physionomie aux relations professionnelles antagonistes et mutualistesSince the end of World War II, worker participation in management has expanded in varying degrees, in different forms, and at different levels. In West Europe both collective bargaining and mutualism have expanded dramatically and workers participation in management seems destined to advance. In Britain and North America the adversary System of collective bargaining has predominated. Mutualistic schemes have been in the small minority. The attitudinal climate has not been conducive to consensus thinking in industrial relations

Right and wrong in labor relations. 14

Cover title."A series of four radio talks delivered during May, 1958, over WILL, the University of Illinois radio station, Urbana.

On Variational Data Assimilation in Continuous Time

Variational data assimilation in continuous time is revisited. The central techniques applied in this paper are in part adopted from the theory of optimal nonlinear control. Alternatively, the investigated approach can be considered as a continuous time generalisation of what is known as weakly constrained four dimensional variational assimilation (WC--4DVAR) in the geosciences. The technique allows to assimilate trajectories in the case of partial observations and in the presence of model error. Several mathematical aspects of the approach are studied. Computationally, it amounts to solving a two point boundary value problem. For imperfect models, the trade off between small dynamical error (i.e. the trajectory obeys the model dynamics) and small observational error (i.e. the trajectory closely follows the observations) is investigated. For (nearly) perfect models, this trade off turns out to be (nearly) trivial in some sense, yet allowing for some dynamical error is shown to have positive effects even in this situation. The presented formalism is dynamical in character; no assumptions need to be made about the presence (or absence) of dynamical or observational noise, let alone about their statistics.Comment: 28 Pages, 12 Figure

Sensitivity And Out-Of-Sample Error in Continuous Time Data Assimilation

Data assimilation refers to the problem of finding trajectories of a prescribed dynamical model in such a way that the output of the model (usually some function of the model states) follows a given time series of observations. Typically though, these two requirements cannot both be met at the same time--tracking the observations is not possible without the trajectory deviating from the proposed model equations, while adherence to the model requires deviations from the observations. Thus, data assimilation faces a trade-off. In this contribution, the sensitivity of the data assimilation with respect to perturbations in the observations is identified as the parameter which controls the trade-off. A relation between the sensitivity and the out-of-sample error is established which allows to calculate the latter under operational conditions. A minimum out-of-sample error is proposed as a criterion to set an appropriate sensitivity and to settle the discussed trade-off. Two approaches to data assimilation are considered, namely variational data assimilation and Newtonian nudging, aka synchronisation. Numerical examples demonstrate the feasibility of the approach.Comment: submitted to Quarterly Journal of the Royal Meteorological Societ

Volunteer Contributions to Montana's Statewide Bat Monitoring Project

Over the last two years, the State of Montana has established a network of passive acoustic monitors to study bat activity patterns at selected locations throughout the state. These monitors, many of which are in remote areas, record bat calls each evening of the year. Their purpose is to document the number and species of bats as a function of time and location, with the intention of generating a statewide database on bat activity. These data could serve as an “early warning system” for the appearance of white-nose syndrome, a deadly fungal infection caused by Geomyces destructans that is ravaging bats in eastern portions of North America. WNS has not been detected in Montana, so the data being presently collected can be considered to be representative of bat behavior in the absence of the disease. A noticeable change in recorded bat activity could be an early indicator of the arrival of WNS. Whether or not WNS reaches Montana, the network is generating an extensive knowledge base about Montana’s bats that will help address a variety of management issues. The Montana caving community has provided help in installing and maintaining the bat monitoring network and in recording observations about bats. Cavers are familiar with the state’s caves, are experienced in working safely in caves, and have an interest in cave biota and the welfare of bats. They are well-suited to assist in a number of capacities, including maintaining the monitoring equipment, recording observations of bats, identifying hibernacula, and installing data loggers. This talk will describe volunteer activities around the state and the partnership between cavers and state organizations to increase the effectiveness of the bat monitoring project

Next generation initiation techniques

Four-dimensional data assimilation strategies can generally be classified as either current or next generation, depending upon whether they are used operationally or not. Current-generation data-assimilation techniques are those that are presently used routinely in operational-forecasting or research applications. They can be classified into the following categories: intermittent assimilation, Newtonian relaxation, and physical initialization. It should be noted that these techniques are the subject of continued research, and their improvement will parallel the development of next generation techniques described by the other speakers. Next generation assimilation techniques are those that are under development but are not yet used operationally. Most of these procedures are derived from control theory or variational methods and primarily represent continuous assimilation approaches, in which the data and model dynamics are 'fitted' to each other in an optimal way. Another 'next generation' category is the initialization of convective-scale models. Intermittent assimilation systems use an objective analysis to combine all observations within a time window that is centered on the analysis time. Continuous first-generation assimilation systems are usually based on the Newtonian-relaxation or 'nudging' techniques. Physical initialization procedures generally involve the use of standard or nonstandard data to force some physical process in the model during an assimilation period. Under the topic of next-generation assimilation techniques, variational approaches are currently being actively developed. Variational approaches seek to minimize a cost or penalty function which measures a model's fit to observations, background fields and other imposed constraints. Alternatively, the Kalman filter technique, which is also under investigation as a data assimilation procedure for numerical weather prediction, can yield acceptable initial conditions for mesoscale models. The third kind of next-generation technique involves strategies to initialize convective scale (non-hydrostatic) models

Improving Incremental Balance in the GSI 3DVAR Analysis System

The Gridpoint Statistical Interpolation (GSI) analysis system is a unified global/regional 3DVAR analysis code that has been under development for several years at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center. It has recently been implemented into operations at NCEP in both the global and North American data assimilation systems (GDAS and NDAS). An important aspect of this development has been improving the balance of the analysis produced by GSI. The improved balance between variables has been achieved through the inclusion of a Tangent Linear Normal Mode Constraint (TLNMC). The TLNMC method has proven to be very robust and effective. The TLNMC as part of the global GSI system has resulted in substantial improvement in data assimilation both at NCEP and at the NASA Global Modeling and Assimilation Office (GMAO)

Data assimilation in the low noise regime with application to the Kuroshio

On-line data assimilation techniques such as ensemble Kalman filters and particle filters lose accuracy dramatically when presented with an unlikely observation. Such an observation may be caused by an unusually large measurement error or reflect a rare fluctuation in the dynamics of the system. Over a long enough span of time it becomes likely that one or several of these events will occur. Often they are signatures of the most interesting features of the underlying system and their prediction becomes the primary focus of the data assimilation procedure. The Kuroshio or Black Current that runs along the eastern coast of Japan is an example of such a system. It undergoes infrequent but dramatic changes of state between a small meander during which the current remains close to the coast of Japan, and a large meander during which it bulges away from the coast. Because of the important role that the Kuroshio plays in distributing heat and salinity in the surrounding region, prediction of these transitions is of acute interest. Here we focus on a regime in which both the stochastic forcing on the system and the observational noise are small. In this setting large deviation theory can be used to understand why standard filtering methods fail and guide the design of the more effective data assimilation techniques. Motivated by our analysis we propose several data assimilation strategies capable of efficiently handling rare events such as the transitions of the Kuroshio. These techniques are tested on a model of the Kuroshio and shown to perform much better than standard filtering methods.Comment: 43 pages, 12 figure