Precommitted Government Spending and Partisan Politics

This paper analyzes government commitments to ongoing spending programs that require future outlays. Spending commitments are important for understanding partisan politics because they constrain future governments. In a model with one government good, a “stubborn liberal” policy maker can use precommitted spending to prevent a later conservative government from imposing decisive spending cuts. In a model where parties differ about spending priorities, reelection uncertainty creates a permanent bias towards higher government spending and higher taxes.government spending, partisan politics, political economy, precommitment

Harnessing technology review 2008. The role of technology and its impact on education. Summary Report.

This is the summary of the second review of the use and impact of ICT in the education system following the publication of the Government's e-Strategy for education, known as Harnessing Technology. The Review drew upon Becta's surveys of schools and FE colleges as well as other research to assess the impact of technology within the education system and the progress made in achieving the system outcomes of the policy

Spartan Daily, November 13, 1950

Volume 39, Issue 33https://scholarworks.sjsu.edu/spartandaily/11454/thumbnail.jp

The Unionization of Clerical, Technical, and Professional Employees in Higher Education: Threat or Opportunity

[Excerpt] Union organizing among non-teaching white collar employees of colleges and universities persists. To the discomfort of many university administrators, high visibility union successes at Yale, Columbia, Harvard, the University of Cincinnati, and the University of Illinois were not isolated instances but part of a trend. Professional, technical, and clerical employees\u27 desire for a more effective voice, has combined with the economic insecurity associated with stubborn budgetary pressures, to encourage these workers to pursue union representation. Unions have responded to this opportunity with enthusiasm, experimenting with innovative organizing and bargaining strategies in the relatively open environment offered by institutions of higher education. This chapter presents a sympathetic summary of this phenomenon. It touches on employee motivation to unionize, models of university white collar organizing, responses to unionization by university administrators, and the range of possible bargaining relationships. The concluding section suggests a management position towards organizing and bargaining consistent with the highest standards of the academy. To set the stage, the essay begins with a descriptive review of the extent of unionization

Accelerating Heuristic Search for AI Planning

AI Planning is an important research field. Heuristic search is the most commonly used method in solving planning problems. Despite recent advances in improving the quality of heuristics and devising better search strategies, the high computational cost of heuristic search remains a barrier that severely limits its application to real world problems. In this dissertation, we propose theories, algorithms and systems to accelerate heuristic search for AI planning. We make four major contributions in this dissertation. First, we propose a state-space reduction method called Stratified Planning to accelerate heuristic search. Stratified Planning can be combined with any heuristic search to prune redundant paths in state space, without sacrificing the optimality and completeness of search algorithms. Second, we propose a general theory for partial order reduction in planning. The proposed theory unifies previous reduction algorithms for planning, and ushers in new partial order reduction algorithms that can further accelerate heuristic search by pruning more nodes in state space than previously proposed algorithms. Third, we study the local structure of state space and propose using random walks to accelerate plateau exploration for heuristic search. We also implement two state-of-the-art planners that perform competitively in the Seventh International Planning Competition. Last, we utilize cloud computing to further accelerate search for planning. We propose a portfolio stochastic search algorithm that takes advantage of the cloud. We also implement a cloud-based planning system to which users can submit planning tasks and make full use of the computational resources provided by the cloud. We push the state of the art in AI planning by developing theories and algorithms that can accelerate heuristic search for planning. We implement state-of-the-art planning systems that have strong speed and quality performance

Personal intelligence

A model of personal intelligence is developed. Personal intelligence is defined as the capacity to reason about personality and to use personality and personal information to enhance one\u27s thoughts, plans, and life experience. Approaches to related concepts such as intrapersonal intelligence and psychological-mindedness are reviewed. Next, a model of personal intelligence is proposed that emphasizes the capacity to: a) recognize personally-relevant information; b) form accurate models of personality; c) guide one\u27s choices by using personality information; and d) systematize one\u27s goals, plans, and life stories. A discussion examines the possible contributions and limitations of the personal intelligence concept

Special Libraries, October 1944

Volume 35, Issue 8https://scholarworks.sjsu.edu/sla_sl_1944/1007/thumbnail.jp