102,503 research outputs found
The Right to Strike under the United States Constitution: Theory, Practice, and Possible Implications for Canada
No full textAnswering critics of the Canadian Supreme Court's judgment in B.C. Health, the author argues that the Court laid the foundation for a principled and durable doctrine protecting constitutional labour rights, one that goes directly to the heart of the matter — the inequality of workers’ power in the employment relation. In the author’s view, two paths could lead from B.C. Health to the recognition of Charter protec- tion for a right to strike: one that treats the right as an accessory to col- lective bargaining, and one that upholds the right directly on the basis of the Charter values of equality and participation. The author supports the latter approach, contending that constitutional rights should be defined in relation to fundamental values, in a way that is not contingent on time-bound or fact-sensitive assessments about the role of strikes within a particular collective bargaining regime. Although a Charter right to strike may involve the courts in difficult choices about when to defer to legislative policy decisions, and courts may lack the institutional capac- ity to deal effectively with labour law issues, the author points out that judges can look to ILO standards for expert guidance. Noting that the U.S. experience in this area might be of considerable use to Canadians, the author concludes by providing an overview of American case law concerning a constitutional right to strike.Peer reviewe
The Effect of Disease-Modifying Drugs on Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: A Meta-Analysis.
No full textThe quantification of brain atrophy in relapsing-remitting multiple sclerosis (RRMS) may serve as a marker of disease progression and treatment response. We compared the association between first-line (FL) or second-line (SL) disease-modifying drugs (DMDs) and brain volume changes over time in RRMS.We reviewed clinical trials in RRMS between January 1, 1995 and June 1, 2014 that assessed the effect of DMDs and reported data on brain atrophy in Medline, Embase, the Cochrane database and meeting abstracts. First, we designed a meta-analysis to directly compare the percentage brain volume change (PBVC) between FLDMDs and SLDMDs at 24 months. Second, we conducted an observational and longitudinal linear regression analysis of a 48-month follow-up period. Sensitivity analyses considering PBVC between 12 and 48 months were also performed.Among the 272 studies identified, 117 were analyzed and 35 (18,140 patients) were included in the analysis. Based on the meta-analysis, atrophy was greater for the use of an FLDMD than that of an SLDMD at 24 months (primary endpoint mean difference, -0.86; 95% confidence interval: -1.57--0.15; P = 0.02). Based on the linear regression analysis, the annual PBVC significantly differed between SLDMDs and placebo (-0.27%/y and -0.50%/y, respectively, P = 0.046) but not between FLDMDs (-0.33%/y) and placebo (P = 0.11) or between FLDMDs and SLDMDs (P = 0.49). Based on sensitivity analysis, the annual PBVC was reduced for SLDMDs compared with placebo (-0.14%/y and -0.56%/y, respectively, P<0.001) and FLDMDs (-0.46%/y, P<0.005), but no difference was detected between FLDMDs and placebo (P = 0.12).SLDMDs were associated with reduced PBVC slope over time in RRMS, regardless of the period considered. These results provide new insights into the mechanisms underlying atrophy progression in RRMS
Bibliographie Hilarion G. Petzold 1958 – 2009 mit Anhang als Einführung
No full textDieses Archiv enthält die Gesamtbibliographie der Werke des Autors nebst einiger Texte „Über H. G. Petzold“ im Schlussteil der Bibliographie sowie einen Anhang mit einer Einführung in die Architektur des Werkes in seinem wissenslogischen Aufbau als Ausarbeitung seines „Tree of Science Modells“ (2007).This archive contains the complete bibliography of the author and some texts about H. G. Petzold, moreover an epilogue with an introduction to the architecture of the works in its epistemological structure and composition and as an elaborations of Petzold’s „Tree of Science Modell (2007).https://www.fpi-publikation.de/polyloge/01-2009-petzold-h-g-gesamtbibliographie-h-g-petzold-1958-2009-updating-november2009/peerReviewedpublishedVersio
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
AI Says I’m Better: Evaluating the Effect of AI Defer on Users. A Study Protocol
No full textThe integration of AI into decision support systems raises concerns about
overreliance and distrust. To address this, we propose an experimental protocol
combining Learning to Defer (LtD)—where AI delegates decisions to humans when
appropriate—and Explainable AI (XAI), which provides users with decision
rationales. Our study investigates how these approaches impact human decision-
making, particularly in high-stakes contexts. Participants will classify noisy images
from ImageNet under three between-subjects conditions: Defer (AI defers to user),
Defer + XAI (AI provides an explanation), and Hidden Delegation (AI involvement
is concealed). Each condition will be tested in neutral and high-stakes scenarios, the
latter framed through narratives emphasizing the danger of misclassification. We
will assess decision accuracy and reaction times, as well as psychological measures
that explore the influence of individual differences (i.e., intolerance to uncertainty
and cognitive styles), and emotions (e.g., emotion regulation, and AI-related
anxiety). We hypothesize that Defer may prompt more analytical thinking,
improving accuracy over Hidden Delegation, while Defer + XAI may further
enhance performance. In contrast, Hidden Delegation could promote reliance on
intuitive processing. We expect higher accuracy and longer response times in high-
stakes conditions. Findings will inform the design of human-AI systems that
optimize user engagement and reliability, particularly in domains like clinical
decision-making
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The 4-6 November 2004 Mediterranean storm. Part I: Cloud properties and related electrification
No full textG-Rank: Unsupervised Continuous Learn-to-Rank for Edge Devices in a P2P Network
No full textRanking algorithms in traditional search engines are powered by enormous training data sets that are meticulously engineered and curated by a centralized entity. Decentralized peer-to-peer (p2p) networks such as torrenting applications and Web3 protocols deliberately eschew centralized databases and computational architectures when designing services and features. As such, robust search-and-rank algorithms designed for such domains must be engineered specifically for decentralized networks, and must be lightweight enough to operate on consumer-grade personal devices such as a smartphone or laptop computer. We introduce G-Rank, an unsupervised ranking algorithm designed exclusively for decentralized networks. We demonstrate that accurate, relevant ranking results can be achieved in fully decentralized networks without any centralized data aggregation, feature engineering, or model training. Furthermore, we show that such results are obtainable with minimal data preprocessing and computational overhead, and can still return highly relevant results even when a user’s device is disconnected from the network. G-Rank is highly modular in design, is not limited to categorical data, and can be implemented in a variety of domains with minimal modification. The results herein show that unsupervised ranking models designed for decentralized p2p networks are not only viable, but worthy of further research.https://github.com/awrgold/G-RankComputer Scienc
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