The Insight-Inference Loop: Efficient Text Classification via Natural Language Inference and Threshold-Tuning [0.03%]
基于自然语言推理和阈值调节的高效文本分类方法
Sandrine Chausson,Marion Fourcade,David J Harding et al.
Sandrine Chausson et al.
Modern computational text classification methods have brought social scientists tantalizingly close to the goal of unlocking vast insights buried in text data-from centuries of historical documents to streams of social media posts. Yet thre...
Migration Status Gradients in Immigrant Poverty: A Comparison of Imputation Methods [0.03%]
移民贫困中的迁移状态差异：替代法的比较
Cody Spence,James D Bachmeier,Claire E Altman et al.
Cody Spence et al.
Research on the stratifying effects of migration status has increased sharply in the last two decades, although efforts have been hampered by the near absence of representative data that include detailed migration status measures. Researche...
The causal effect of parent occupation on child occupation: A multivalued treatment with positivity constraints [0.03%]
家长职业对子女职业的因果影响：多值处理与正性约束
Ian Lundberg,Daniel Molitor,Jennie E Brand
Ian Lundberg
To what degree does parent occupation cause a child's occupational attainment? We articulate this causal question in the potential outcomes framework. Empirically, we show that adjustment for only two confounding variables substantially red...
Promises and Limits of Using Targeted Social Media Advertising to Sample Global Migrant Populations: Nigerians at Home and Abroad [0.03%]
针对移居人群的社会媒体抽样调查的机遇与局限性：境内和境外尼日利亚人的案例研究
Thomas Soehl,Zhenxiang Chen,Aaron Erlich
Thomas Soehl
Survey research on migrants is notoriously challenging, especially if the goal is to collect data across a range of countries. Social networking sites' ability to micro-target advertisements to migrant communities combined with their near-g...
The Target Study: A Conceptual Model and Framework for Measuring Disparity [0.03%]
目标研究：测量差异的概念模型与框架
John W Jackson,Yea-Jen Hsu,Raquel C Greer et al.
John W Jackson et al.
We present a conceptual model to measure disparity-the target study-where social groups may be similarly situated (i.e., balanced) on allowable covariates. Our model, based on a sampling design, does not intervene to assign social group mem...
Opening the Blackbox of Treatment Interference: Tracing Treatment Diffusion through Network Analysis [0.03%]
打开治疗干扰的黑箱：通过网络分析追踪治疗扩散
Weihua An,Tyler J VanderWeele
Weihua An
Causal inference under treatment interference is a challenging but important problem. Past studies usually make strong assumptions on the structure of treatment interference in order to estimate causal treatment effects while accounting for...
The gap-closing estimand: A causal approach to study interventions that close disparities across social categories [0.03%]
差距闭合估计量：一种研究关闭不同社会类别差异的干预措施的因果方法
Ian Lundberg
Ian Lundberg
Disparities across race, gender, and class are important targets of descriptive research. But rather than only describe disparities, research would ideally inform interventions to close those gaps. The gap-closing estimand quantifies how mu...
Maximizing Utility or Avoiding Losses? Uncovering Decision Rule-Heterogeneity in Sociological Research with an Application to Neighbourhood Choice [0.03%]
最大化效用还是避免损失？利用社会学研究中的决策规则异质性及其在邻里选择中的应用
Ulf Liebe,Sander van Cranenburgh,Caspar Chorus
Ulf Liebe
Empirical studies on individual behaviour often, implicitly or explicitly, assume a single type of decision rule. Other studies do not specify behavioural assumptions at all. We advance sociological research by introducing (random) regret m...
Theoretical foundations and limits of word embeddings: What types of meaning can they capture? [0.03%]
词嵌入的理论基础和局限性：它们能捕捉什么样的含义？
Alina Arseniev-Koehler
Alina Arseniev-Koehler
Measuring meaning is a central problem in cultural sociology and word embeddings may offer powerful new tools to do so. But like any tool, they build on and exert theoretical assumptions. In this paper I theorize the ways in which word embe...
How Many Imputations Do You Need? A Two-stage Calculation Using a Quadratic Rule [0.03%]
你需要多少次填充？两步计算的二次规则
Paul T von Hippel
Paul T von Hippel
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imp...