105,067 research outputs found

    Open Letter to Bureau Veritas’ CEO, Frank Piedelievre

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    This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide.  Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.CLW_OpenLetter_BV.pdf: 219 downloads, before Oct. 1, 2020

    Take Action! Urge Wal-Mart to Publicly: Respond to Violations in its Supply Chain

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    This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.CLW_2009_Report_China_take_action_wal_mart.pdf: 16 downloads, before Oct. 1, 2020

    On the Wa Yaobao Mine Disaster

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    This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.CLW_2006_Report_China_On_the_Wa.pdf: 11 downloads, before Oct. 1, 2020

    Li Qiang\u27s Speech Given at Albert Shanker Institute\u27s China Seminar

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    Distributions of full and non-full words in beta-expansions

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    The structures of full words and non-full for β\beta-expansions are completely characterized in this paper. We obtain the precise lengths of all the maximal runs of full and non-full words among admissible words with same order

    Cheaper and Better: Selecting Good Workers for Crowdsourcing

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    Crowdsourcing provides a popular paradigm for data collection at scale. We study the problem of selecting subsets of workers from a given worker pool to maximize the accuracy under a budget constraint. One natural question is whether we should hire as many workers as the budget allows, or restrict on a small number of top-quality workers. By theoretically analyzing the error rate of a typical setting in crowdsourcing, we frame the worker selection problem into a combinatorial optimization problem and propose an algorithm to solve it efficiently. Empirical results on both simulated and real-world datasets show that our algorithm is able to select a small number of high-quality workers, and performs as good as, sometimes even better than, the much larger crowds as the budget allows
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