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LGBTQ+ Identification in U.S. Now at 7.6%

Gallup, Inc., Jeffrey M. Jones

Gallup.com·2024

LGBTQ+ identification in the U.S. continues to inch up, with 7.6% of all U.S. adults, and more than one in five Gen Z adults, identifying this way.

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Lifetime and Past-Year Defensive Gun Use

Michael D. Anestis, Kimberly Burke, Sultan Altikriti, Daniel Semenza

JAMA Network Open·2025·4 citations

Key Points Question What are the frequency, distribution, and factors associated with defensive gun use? Findings In this survey study of 3000 adults with firearm access, most (91.7%) reported no lifetime history of defensive gun use, whereas many reported lifetime gun violence exposure. Individuals exposed to gun violence and who carried firearms more frequently and stored firearms loaded and unlocked were more likely to report prior defensive gun use. Meaning These findings suggest that policy conversations that center the defensive gun use misstate the risk profile of firearm access.

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Misogynistic Language on Twitter and Sexual Violence

Rachael Fulper, Giovanni Luca Ciampaglia, Emilio Ferrara, 1 YongYeol Ahn, Alessandro Flammini, Filippo Menczer

figshare.com·2015

Studies have demonstrated that social media may offer insights into social behaviors. Here we investigate the potential of social media in predicting criminal behavior, in particular rape and sexual abuse. Traditional approaches for studying sexual violence are effective but laborious, although often limited to small sample sizes and coarse temporal resolutions. Additionally, the sensitive nature of sexual violence and stigmas against victims result in serious underreporting ofrapecrimestatistics. Thefactorscontributingtorapearenot fullyagreedupon, but researchshowsthat theacceptanceof,andwillingnessto commit rapearehighlycorrelatedwithsexrolestereotyping,rapemythbeliefs,andmisogyny.Hereweexplorewhethersocial mediacanbeusedasanindicatorofsexualviolenceintheUS,bytrackingmisogynistictweets.Wecomparedthenumberof tweetsandrapecrimestatisticsforeachstate,andfoundasignificantassociation.Ourworkpavesthewaytothedesignofa ‘social sensor’ system to detect rape and other abuse by monitoring social streams.

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von Willebrand disease

Omid Seidizadeh, Jeroen C. J. Eikenboom, Cécile V. Denis, Veronica H. Flood, Paula James, Peter J. Lenting, Luciano Baronciani, James S. O’Donnell, David Lillicrap, Flora Peyvandi

Nature Reviews Disease Primers·2024·31 citations

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Notes on the Index: Seventies Art in America

Rosalind Krauss

October·1977·81 citations

At the forefront of contemporary arts criticism and theory, October focuses critical attention on the contemporary arts and their various contexts of interpretation: film, painting, music, photography, performance, sculpture, and literature. Examining relationships between the arts and their critical and social contexts, October addresses a broad range of readers. Original, innovative, provocative, each issue presents the best, most current texts by and about today's artistic, intellectual, and critical vanguard.

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Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study

Yotam Alexander, Yonatan Slutzky, Yuval Ran-Milo, Nadav Cohen

arXiv·2025

Conventional wisdom attributes the mysterious generalization abilities of overparameterized neural networks to gradient descent (and its variants). The recent volume hypothesis challenges this view: it posits that these generalization abilities persist even when gradient descent is replaced by Guess & Check (G&C), i.e., by drawing weight settings until one that fits the training data is found. The validity of the volume hypothesis for wide and deep neural networks remains an open question. In this paper, we theoretically investigate this question for matrix factorization (with linear and non-linear activation)--a common testbed in neural network theory. We first prove that generalization under G&C deteriorates with increasing width, establishing what is, to our knowledge, the first case where G&C is provably inferior to gradient descent. Conversely, we prove that generalization under G&C improves with increasing depth, revealing a stark contrast between wide and deep networks, which we further validate empirically. These findings suggest that even in simple settings, there may not be a simple answer to the question of whether neural networks need gradient descent to generalize well.

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When does a predictor know its own loss?

Aravind Gollakota, Parikshit Gopalan, Aayush Karan, Charlotte Peale, Udi Wieder

arXiv·2025

Given a predictor and a loss function, how well can we predict the loss that the predictor will incur on an input? This is the problem of loss prediction, a key computational task associated with uncertainty estimation for a predictor. In a classification setting, a predictor will typically predict a distribution over labels and hence have its own estimate of the loss that it will incur, given by the entropy of the predicted distribution. Should we trust this estimate? In other words, when does the predictor know what it knows and what it does not know? In this work we study the theoretical foundations of loss prediction. Our main contribution is to establish tight connections between nontrivial loss prediction and certain forms of multicalibration, a multigroup fairness notion that asks for calibrated predictions across computationally identifiable subgroups. Formally, we show that a loss predictor that is able to improve on the self-estimate of a predictor yields a witness to a failure of multicalibration, and vice versa. This has the implication that nontrivial loss prediction is in effect no easier or harder than auditing for multicalibration. We support our theoretical results with experiments that show a robust positive correlation between the multicalibration error of a predictor and the efficacy of training a loss predictor.

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Highest Rated Papers

LGBTQ+ Identification in U.S. Now at 7.6%

Lifetime and Past-Year Defensive Gun Use

Misogynistic Language on Twitter and Sexual Violence

von Willebrand disease

A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants

Convention on Biodiversity | United Nations

Notes and Analysis on: Zionist Colonization of Palestine, by Fayez Sayegh.

Analisis Aksesibilitas Bus Rapid Transit Bagi Penumpang dengan Disabilitas di DKI Jakarta: Studi Kasus Pada Moda Transportasi Publik di DKI Jakarta - Universitas Indonesia

Notes on the Index: Seventies Art in America

Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study

Moralization in social networks and the emergence of violence during protests

When does a predictor know its own loss?