233 research outputs found

    Our Forgotten Founders: Reconstruction, Public Education, and Constitutional Heroism

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    In this Article, I consider the constitutional stories we tell our schoolchildren about the Founding and Reconstruction. To that end, I analyze the relevant sections of our leading high school history textbooks, focusing particularly on the consensus narratives and constitutional heroes that emerge in these accounts. This analysis is vital to more fully understanding the background assumptions that elite lawyers, political leaders, and the wider public bring to bear when they consider the meaning of the Constitution

    Popular Constitutional Argument

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    Critics have long attacked popular constitutionalists for offering few clues about how their theory might work in practice—-especially inside the courts. These critics are right. Popular constitutionalism—as a matter of both theory and practice—remains a work in progress. In this Article, I take up the challenge of developing an account of (what I call) popular constitutional argument. Briefly stated, popular constitutional argument is a form of argument that draws on the American people’s considered judgments as a source of constitutional authority—akin to traditional sources like text, history, structure, and doctrine. Turning to constitutional theory, I situate popular constitutional argument within contemporary debates over judicial restraint, living constitutionalism, popular sovereignty theory, and originalism. And turning to constitutional practice, I offer the interpreter a concrete framework for crafting popular constitutional arguments— cataloguing the various indicators of public opinion that have played a role in recent Supreme Court decisions. These indicators include measures associated with the president, Congress, state and local governments, the American people’s actions and traditions, and public opinion polls. Throughout, I use illustrative examples to show the various ways in which popular constitutional argument already operates at the Supreme Court—appealing to jurists from across the ideological spectrum. While this Article begins to explore how popular constitutionalism might operate inside the courts, much work remains

    Judicial Popular Constitutionalism

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    Book review: We the people, Volume 3: the civil rights revolution. By Bruce Ackerman. 2014. Belknap Press of Harvard University Press. 432 pages. Reviewed by Tom Donnell

    Our Forgotten Founders: Reconstruction, Public Education, and Constitutional Heroism

    Get PDF
    In this Article, I consider the constitutional stories we tell our schoolchildren about the Founding and Reconstruction. To that end, I analyze the relevant sections of our leading high school history textbooks, focusing particularly on the consensus narratives and constitutional heroes that emerge in these accounts. This analysis is vital to more fully understanding the background assumptions that elite lawyers, political leaders, and the wider public bring to bear when they consider the meaning of the Constitution

    Renault-Nissan: East meets West

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    The DaimlerChrysler Mitsubishi merger: a study in failure

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    Rover-BMW: study in merger failure

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    Denoising and decoding spontaneous vagus nerve recordings with machine learning

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    Neural interfaces that electrically stimulate the peripheral nervous system have been shown to successfully improve symptom management for several conditions, such as epilepsy and depression. A crucial part for closing the loop and improving the efficacy of implantable neuromodulation devices is the efficient extraction of meaningful information from nerve recordings, which can have a low Signal-to-Noise ratio (SNR) and non-stationary noise. In recent years, machine learning (ML) models have shown outstanding performance in regression and classification problems, but it is often unclear how to translate and assess these for novel tasks in biomedical engineering. This paper aims to adapt existing ML algorithms to carry out unsupervised denoising of neural recordings instead. This is achieved by applying bandpass filtering and two novel ML algorithms to in-vivo spontaneous, low-SNR vagus nerve recordings. The performance of each approach is compared using the task of extracting respiratory afferent activity and validated using cross-correlation, MSE, and accuracy in terms of extracting the true respiratory rate. A variational autoencoder (VAE) model in particular produces results that show better correlation with respiratory activity compared to bandpass filtering, highlighting that these models have the potential to preserve relevant features in complex neural recordings
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