Use Of Contextual Data Research Articles

Inertia in elite STEM widening participation: the use of contextual data in admissions

There is a contradiction of intensive national policy efforts and the slow pace of change in widening participation in England. This paper focuses on the use of contextual data in STEM subjects, where there has been less progress in widening access and a more rigid entry pathway through A-level study. Interviews with admissions tutors suggest a narrative in which STEM curricula, and the prior knowledge and skills required to succeed within it are fixed, and that attempts to widen participation and broaden the notion of ‘best students’ could undermine academic standards and the student experience. The paper draws on social justice and social reproduction theoretical frameworks to explore policy enactment, identifying support for widening participation and the effects of a conservative ethos amongst academics. The tension of these approaches, alongside the autonomy of decision-makers, are key dynamics explaining the inertia of policy efforts for change.

BERT for Conversational Question Answering Systems Using Semantic Similarity Estimation

Most of the questions from users lack the context needed to thoroughly understand the problem at hand, thus making the questions impossible to answer. Semantic Similarity Estimation is based on relating user’s questions to the context from previous Conversational Search Systems (CSS) to provide answers without requesting the user's context. It imposes constraints on the time needed to produce an answer for the user. The proposed model enables the use of contextual data associated with previous Conversational Searches (CS). While receiving a question in a new conversational search, the model determines the question that refers to more past CS. The model then infers past contextual data related to the given question and predicts an answer based on the context inferred without engaging in multi-turn interactions or requesting additional data from the user for context. This model shows the ability to use the limited information in user queries for best context inferences based on Closed-Domain-based CS and Bidirectional Encoder Representations from Transformers for textual representations.

A Data-Driven Multiobjective Optimization Framework for Hyperdense 5G Network Planning

The trials and rollout of the fifth generation (5G) network technologies are gradually intensifying as 5G is positioned as a platform that not only accommodates exploding data traffic but also unlocks a multitude use cases, services and deployment scenarios. However, the need for hyperdense 5G deployments is revealing some of the limitations of planning approaches that hitherto proved adequate for pre-5G systems. The hyperdensification envisioned in 5G networks not only adds complexity to network planning and optimization problems, but underlines need for more realistic data-driven approaches that consider cost, varying demands and other contextual attributes to produce feasible topologies. Furthermore, the quest for network programmability and automation including the 5G radio access network (RAN), as manifested by network slicing technologies and more flexible RAN architectures, are also among other factors that influence planning and optimization frameworks. Collectively, these deployment trends, technological developments and evolving (and diverse) service demands point towards the need for more holistic frameworks. This article proposes a data-driven multiobjective optimization framework for hyperdense 5G network planning with practical case studies used to illustrate added value compared to contemporary network planning and optimization approaches. Comparative results from the case study with real network data reveal potential performance and cost improvements of hyperdense optimized networks produced by the proposed framework due to increased use of contextual data of planning area and focus on objectives that target demand satisfaction.

Contextual factors in maternal and newborn health evaluation: a protocol applied in Nigeria, India and Ethiopia

BackgroundUnderstanding the context of a health programme is important in interpreting evaluation findings and in considering the external validity for other settings. Public health researchers can be imprecise and inconsistent in their usage of the word “context” and its application to their work. This paper presents an approach to defining context, to capturing relevant contextual information and to using such information to help interpret findings from the perspective of a research group evaluating the effect of diverse innovations on coverage of evidence-based, life-saving interventions for maternal and newborn health in Ethiopia, Nigeria, and India.MethodsWe define “context” as the background environment or setting of any program, and “contextual factors” as those elements of context that could affect implementation of a programme. Through a structured, consultative process, contextual factors were identified while trying to strike a balance between comprehensiveness and feasibility. Thematic areas included demographics and socio-economics, epidemiological profile, health systems and service uptake, infrastructure, education, environment, politics, policy and governance. We outline an approach for capturing and using contextual factors while maximizing use of existing data. Methods include desk reviews, secondary data extraction and key informant interviews. Outputs include databases of contextual factors and summaries of existing maternal and newborn health policies and their implementation. Use of contextual data will be qualitative in nature and may assist in interpreting findings in both quantitative and qualitative aspects of programme evaluation.DiscussionApplying this approach was more resource intensive than expected, in part because routinely available information was not consistently available across settings and more primary data collection was required than anticipated. Data was used only minimally, partly due to a lack of evaluation results that needed further explanation, but also because contextual data was not available for the precise units of analysis or time periods of interest. We would advise others to consider integrating contextual factors within other data collection activities, and to conduct regular reviews of maternal and newborn health policies. This approach and the learnings from its application could help inform the development of guidelines for the collection and use of contextual factors in public health evaluation.

Using social network and ethnographic tools to evaluate syphilis transmission.

Partner notification has been the cornerstone for the prevention and control of syphilis in the United States. This technique may not make full use of contextual data that an ethnographic and social network approach can offer. The occasion of a syphilis outbreak among young people was used to investigate the applicability of a social network approach and to test the validity of several traditional approaches to syphilis epidemiology. An outbreak of syphilis was investigated by interviewing both infected and noninfected people, by directing resources based on network association, by creating and evaluating network diagrams as an aid to the epidemiologic process, and by including ethnographic observations as part of outbreak management. Diagrammatic display of network growth provided a useful alternative to the traditional epidemic curve. Case prevention was demonstrated by identifying uninfected people with multiple concurrent exposures. Concurrent, overlapping exposure in infected people rendered traditional "source" and "spread" criteria moot. The current discussions of partner notification may be informed by recognizing that it is a subset of a broader and potentially more powerful approach. This approach calls some basic tenets of syphilis epidemiology into question.

Nonverbal courtship patterns in women: Context and consequences

There is a class of nonverbal facial expressions and gestures, exhibited by human females, that are commonly labeled “flirting behaviors.” I observed more than 200 randomly selected adult female subjects in order to construct a catalog of these nonverbal solicitation behaviors. Pertinent behaviors were operationally defined through the use of consequential data; these behaviors elicited male attention. Fifty-two behaviors were described using this method. Validation of the catalog was provided through the use of contextual data. Observations were conducted on 40 randomly selected female subjects in one of four contexts: a singles' bar, a university snack bar, a university library, and at university Women's Center meetings. The results indicated that women in “mate relevant” contexts exhibited higher average frequencies of nonverbal displays directed at males. Additionally, women who signaled often were also those who were most often approached by a man: and this relationship was not context specific. I suggest that the observation of women in field situations may provide clues to criteria used by females in the initial selection of male partners. As much of the work surrounding human attraction has involved laboratory studies or data collected from couples in established relationships, the observation of nonverbal behavior in field settings may provide a fruitful avenue for the exploration of human female choice in the preliminary stages of male-female interaction.