The Impossibility of “Freedom as Independence”

Most of the recent work on freedom is concerned with the liberal-republican debate. The latest move in this debate has been made by List and Valentini who argue in favor of a conception of freedom (called "freedom as independence") that is located midway between the liberal and republican conceptions. In this article, we review some key aspects of the debate that led to List and Valentini's move and then argue that their midway position is untenable. We first show how the debate has given rise to List and Valentini's (republican-inspired) view that unfreedom is created not merely by more or less probable constraints (as liberals have claimed) but by the sheer possibility of constraints. We then argue that this position on possible-but-improbable constraints makes unfreedom ubiquitous and that "freedom as independence" is therefore an impossible ideal. In the course of our argument, we rebut some possible rejoinders that appeal to the difference between positive normative and non-normative constraints and to the ways in which "freedom as independence" is an open and versatile concept

Comparison of Failure Detectors and Group Membership: Performance Study of Two Atomic Broadcast Algorithms

Protocols that solve agreement problems are essential building blocks for fault tolerant distributed systems. While many protocols have been published, little has been done to analyze their performance, especially the performance of their fault tolerance mechanisms. In this paper, we present a performance evaluation methodology that can be generalized to analyze many kinds of fault-tolerant algorithms. We use the methodology to compare two atomic broadcast algorithms with different fault tolerance mechanisms: unreliable failure detectors and group membership. We evaluated the steady state latency in (1) runs with no crashes and no suspicions, (2) runs with crashes and (3) runs with no crashes in which correct processes are wrongly suspected to have crashed, as well as (4) the transient latency after a crash. We found that the two algorithms have the same performance in Scenario 1, and that the group membership based algorithm has an advantage in terms of performance and resiliency in Scenario 2, whereas the failure detector based algorithm offers better performance in the other scenarios. We discuss the implications of our results to the design of fault tolerant distributed systems

Comparison of Failure Detectors and Group Membership: Performance Study of Two Atomic Broadcast Algorithms (extended version)

Protocols that solve agreement problems are essential building blocks for fault tolerant distributed systems. While many protocols have been published, little has been done to analyze their performance, especially the performance of their fault tolerance mechanisms. In this paper, we present a performance evaluation methodology that can be generalized to analyze many kinds of fault-tolerant algorithms. We use the methodology to compare two atomic broadcast algorithms with different fault tolerance mechanisms: unreliable failure detectors and group membership. We evaluated the steady state latency in (1) runs with neither crashes nor suspicions, (2) runs with crashes and (3) runs with no crashes in which correct processes are wrongly suspected to have crashed, as well as (4) the transient latency after a crash. We found that the two algorithms have the same performance in Scenario 1, and that the group membership based algorithm has an advantage in terms of performance and resiliency in Scenario 2, whereas the failure detector based algorithm offers better performance in the other scenarios. We discuss the implications of our results to the design of fault tolerant distributed systems

Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours

Text classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a custom classifier typically requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier, we introduce Label Sleuth, a free open source system for labeling and creating text classifiers. This system is unique for (a) being a no-code system, making NLP accessible to non-experts, (b) guiding users through the entire labeling process until they obtain a custom classifier, making the process efficient -- from cold start to classifier in a few hours, and (c) being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will broaden the utilization of NLP models.Comment: 7 pages, 2 figure

Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures

Many different performance measures have been developed to evaluate field predictions in meteorology. However, a researcher or practitioner encountering a new or unfamiliar measure may have difficulty in interpreting its results, which may lead to them avoiding new measures and relying on those that are familiar. In the context of evaluating forecasts of extreme events for hydrological applications, this article aims to promote the use of a range of performance measures. Some of the types of performance measures that are introduced in order to demonstrate a six-step approach to tackle a new measure. Using the example of the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble precipitation predictions for the Danube floods of July and August 2002, to show how to use new performance measures with this approach and the way to choose between different performance measures based on their suitability for the task at hand is shown. Copyright © 2008 Royal Meteorological Societ