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Titlebook: Making ‘Postmodern‘ Mothers; Pregnant Embodiment, Meredith Nash Book 2012 Palgrave Macmillan, a division of Macmillan Publishers Limited 20

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发表于 2025-3-21 18:53:52 | 显示全部楼层 |阅读模式
书目名称Making ‘Postmodern‘ Mothers
副标题Pregnant Embodiment,
编辑Meredith Nash
视频video
丛书名称Genders and Sexualities in the Social Sciences
图书封面Titlebook: Making ‘Postmodern‘ Mothers; Pregnant Embodiment, Meredith Nash Book 2012 Palgrave Macmillan, a division of Macmillan Publishers Limited 20
描述Based on interviews with pregnant women, this book provides a multi-disciplinary empirical account of pregnant embodiment and how it relates to wider sociological and feminist discourses about gender, bodies, ‘fitness‘, ‘fat‘, celebrity and motherhood.
出版日期Book 2012
关键词feminism; gender; Image; sociology; women
版次1
doihttps://doi.org/10.1057/9781137292155
isbn_softcover978-1-349-34713-1
isbn_ebook978-1-137-29215-5Series ISSN 2947-8782 Series E-ISSN 2947-8790
issn_series 2947-8782
copyrightPalgrave Macmillan, a division of Macmillan Publishers Limited 2012
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Meredith Nash scarce. While many of these approaches rely on a cross-entropy loss function (CE), recent advances have shown that the supervised contrastive loss function (SupCon) can be more effective. Additionally, unsupervised contrastive learning approaches have also been shown to capture high quality data re
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Meredith Nashng methods for learning user representations are usually based on supervised frameworks such as demographic prediction and product recommendation. In addition, these methods highly rely on labeled data to learn user-representation models, and the user representations learned using these methods can
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发表于 2025-3-23 00:16:51 | 显示全部楼层
Meredith Nashcommerce to computational biology. However, generating satisfactory video embeddings and putting them into practical use to improve the performance of recommendation tasks remains a challenge. In this paper, we present a video embedding approach named Equuleus, which learns video embeddings from use
发表于 2025-3-23 04:59:06 | 显示全部楼层
Meredith Nashnd reliable prediction crucial for mitigating potential impacts. This paper contributes to the growing body of research on deep learning methods for solar flare prediction, primarily focusing on highly overlooked near-limb flares and utilizing the attribution methods to provide a post hoc qualitativ
发表于 2025-3-23 08:54:59 | 显示全部楼层
Meredith Nashin analyzing complex control flows. Current machine learning systems, mostly based on artificial neural networks, have the inherent problem that models cannot be verified since the decisions depend on probabilities. To bridge the gap between handcrafted rule systems and probability-based systems, ou
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