![]() Conclusions: Sexual health interventions for college students should focus on communication and pleasure. Substance use and partner age were associated with outcomes differently by gender. Factors associated with pleasure, control, and communication included partner type and emotional closeness. 72.5% were described as very pleasurable, 26.6% as lacking communication, and 9.1% as lacking control. Results: 1,664 sexual encounters were reported. Methods: 427 college students participated in a 60-day daily survey 213 reported sex and were asked questions about each sexual encounter. ![]() This study aimed to understand situational predictors of various dimensions of students’ sexual experiences. Conclusions: Sexual health interventions for college students should focus on communication and pleasure.ĪB - Objectives: Research examining sex among college students has frequently focused on negative sexual experiences. Methods: 427 college students participated in a 60-day daily survey 213 reported sex and were asked questions about each sexual encounter. The results agree with those of Ghazzawi, Shoughari and Osta (2017) who looked at the situational leadership and its effectiveness in rising employee productivity and revealed a positive. N2 - Objectives: Research examining sex among college students has frequently focused on negative sexual experiences. The authors thank our research participants the Undergraduate Advisory Board Columbia University, and the entire SHIFT team who contributed to the development and implementation of this ambitious effort particularly our Program Director, Leigh Reardon, and quantitative research assistants Karimata Bah and Stephanie Benson. This research was funded by Columbia University through generous support from multiple donors. These results indicate the importance of situational context for personal search, and open up a venue for further exploration of situational context in other search scenarios.T1 - The Situational Contexts of Sexual Experiences among Urban College Students The experiments demonstrate that the proposed models significantly outperform the baselines which do not take context into account. We evaluate our models using the click data collected from one of the world's largest personal search engines. The focus of this paper, personal search (e.g., email search or on-device search) is one of such scenarios. ![]() This distinction between linguistic and situational contexts is frequently labelled by the. Although context-aware models have been widely explored in web search, their influence on search scenarios where click data is highly sparse is relatively unstudied. The more explicit 'context of situation' captures this meaning. The existing context-aware ranking models are mainly based on search history, especially click data that can be gathered from the search engine logs. The second model extends the first model by leveraging binarized contextual features in addition to the high-level abstractions learned from a deep network. The first model learns a low-dimensional deep representation from the combination of contextual features. You will work in pairs to create examples that would illustrate how situational context can influence. We propose two context-aware ranking models based on neural networks. situational context can influence communication. ![]() As an example, situational context can depend on search request time and location. In this paper, we focus on situational context, i.e., the contextual features of the current search request that are independent from both query content and user history. Previously, query context was mainly modeled by user search history, either long-term or short-term, to help the ranking of future queries. Among them, query context has attracted attention in prior work. Modern search engines leverage a variety of sources, beyond the traditional query-document content similarity, to improve their ranking performance.
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