The Pig Story (Tiboi Sakkoko) Storytelling of Kinship, Memories of the Past, and Rights to Plots of Ancestral Land in Mentawai

This paper examines some significant elements of the pig story (tiboi sakkoko). This tale contains crucial information about the collective identity, ancestors and historical events affecting particular Mentawai kin-groups. As families do not preserve their culture and traditions in written form, storytellers of kin-groups have narrated the pig story from generation to generation so as to preserve it carefully. In the course of time, storytellers establish particular ways of telling their stories so as to remember the content and plot of the stories easily. Through the pig story, members of kin groups also recollect their ancestral place of origin and plots of ancestral lands. The role of human memory is indispensable to recalling all these important elements. Therefore, this paper analyses memories of the past of different family generations. To achieve its aims, this paper also evaluates the roles of family stories in the culture and traditions of Mentawai society

Controllable Neural Story Plot Generation via Reinforcement Learning

Language-modeling--based approaches to story plot generation attempt to construct a plot by sampling from a language model (LM) to predict the next character, word, or sentence to add to the story. LM techniques lack the ability to receive guidance from the user to achieve a specific goal, resulting in stories that don't have a clear sense of progression and lack coherence. We present a reward-shaping technique that analyzes a story corpus and produces intermediate rewards that are backpropagated into a pre-trained LM in order to guide the model towards a given goal. Automated evaluations show our technique can create a model that generates story plots which consistently achieve a specified goal. Human-subject studies show that the generated stories have more plausible event ordering than baseline plot generation techniques.Comment: Published in IJCAI 201

A Contextual-Bandit Approach to Personalized News Article Recommendation

Personalized web services strive to adapt their services (advertisements, news articles, etc) to individual users by making use of both content and user information. Despite a few recent advances, this problem remains challenging for at least two reasons. First, web service is featured with dynamically changing pools of content, rendering traditional collaborative filtering methods inapplicable. Second, the scale of most web services of practical interest calls for solutions that are both fast in learning and computation. In this work, we model personalized recommendation of news articles as a contextual bandit problem, a principled approach in which a learning algorithm sequentially selects articles to serve users based on contextual information about the users and articles, while simultaneously adapting its article-selection strategy based on user-click feedback to maximize total user clicks. The contributions of this work are three-fold. First, we propose a new, general contextual bandit algorithm that is computationally efficient and well motivated from learning theory. Second, we argue that any bandit algorithm can be reliably evaluated offline using previously recorded random traffic. Finally, using this offline evaluation method, we successfully applied our new algorithm to a Yahoo! Front Page Today Module dataset containing over 33 million events. Results showed a 12.5% click lift compared to a standard context-free bandit algorithm, and the advantage becomes even greater when data gets more scarce.Comment: 10 pages, 5 figure

Continuous serial - a definition

No abstract available

Perspectives on Deepening Teachers’ Mathematics Content Knowledge: The Case of the Oregon Mathematics Leadership Institute

The Oregon Mathematics Leadership Institute (OMLI) project served 180 Oregon teachers, and 90 administrators, across the K-12 grades from ten partner districts. OMLI offered a residential, three-week summer institute. Over the course of three consecutive summers, teachers were immersed in a total of six mathematics content classes– Algebra, Data & Chance, Discrete Mathematics, Geometry, Measurement & Change, and Number & Operations—along with an annual collegial leadership course. Each content class was designed and taught by a team of expert faculty from universities, community colleges, and K-12 districts. Each team chose a few “big ideas” on which to focus the course. For example, the Algebra team focused on algebraic structure and properties of the concept of a group, while the Data & Chance team centered their activities on the exploration of ideas of central tendency and variation using statistics and data analysis software packages. The content in all of the courses was addressed through deep investigation of the mathematics of tasks that had been selected and adapted from resources for K-12 mathematics classrooms. In addition to mathematics content, the courses were designed with specific attention to socio-mathematical norms, issues of status differences among learners, and the selection and implementation of group-worthy tasks for group work. The faculty attended sessions grounded in the work of Elizabeth Cohen on strategies for working with heterogeneous groups of learners (Cohen, 1994; Cohen et al, 1999) which was central to the OMLI design and implementation. Institute faculty modeled these strategies in the Institute classrooms and made their moves as transparent as possible, so that the teachers would be able to grapple with these strategies during the Institute and plan for implementation in their own classrooms. The Data & Chance course also modeled uses of technology in instruction using Tinkerplots. Generalization and justification were emphasized as mathematical ways of learning and knowing, and institute faculty conducted classroom discussions that intentionally modeled pushing for generalization and justification

Reading Shakespeare's Stage Directions

Suggests that we should consider the stage directions in Shakespeare's early texts, particularly the 1623 Folio, as snippets of narrative or free indirect discourse, rather than as clues to or for performance

American terror:from Oklahoma City to 9/11 and after

Throughout American history, both terrorism and extremism have been constructed, evoked or ignored strategically by the state, media and public at different points, in order to disown and demonize political movements whenever their ideologies and objectives become problematic or inconvenient – because they overlap with, and thus compromise, the legitimacy of the dominant ideology and democratic credentials of the state, because they conflict with the dominant ideology or hegemonic order, because they offend the general (voting) public, or because they expose the fallacies of national unity and bi-polar opposition in the face of foreign enemies or international conflicts, such as the war on terror. This chapter looks at how domestic extreme right terrorism has been constructed, represented, evoked or ignored in the American political imagination in the post-civil rights era, with a particular focus on its changing status following the Oklahoma City bombing and 9/11

The Official Student Newspaper of UAS

Editorial / Whalesong Staff -- Letters to the Editor -- Holiday Expectations -- Perseverance Theatre's Hold These Truths -- Legislators Look at Finance / The Symposium Continued -- UAS In Brief -- UAS Community Thanksgiving --A Time to Remember: The Christmas Truces -- School of Ed. Future Uncertain -- Fantastic Beasts, Unimaginative Writing -- Calendar and Comics