The Effects of Connecting Rituals on Verbal Conflicts in the Montessori Preschool Classroom

The purpose of this action research project was to see if a program through Conscious Discipline called Connecting Rituals would decrease the number of verbal conflicts in a Montessori preschool classroom. Conscious Discipline is a non-punitive, non-adversarial behavior program that is backed by current brain science. One aspect of the Conscious Discipline model is Connecting Rituals. Connecting Rituals are short games, nursery rhymes, and finger plays that adults and children do together in large or small groups. The Connecting Rituals would increase self-regulation and social skills in a Montessori preschool classroom. The study was conducted in a Montessori preschool classroom at a small Montessori school in the Midwestern United States with 23 preschool children, 2.5-6 years old children. Data was collected over a 4 week period using tally marks to record the number of conflicts, a large group discussion, a teacher daily journal and a post-connecting ritual form. Every day the researcher did a Connecting Ritual at the large group gathering with all the children before lunch and at least one Connecting Ritual with each child during the morning work time over a two week period. The study found that the Connecting Rituals did decrease the number of verbal conflicts, but the results were not significant. Further study is needed to understand the long term effects of using Connecting Rituals in the classroom

Jews in the Soviet Union, citizens and builders

https://stars.library.ucf.edu/prism/1459/thumbnail.jp

Do Fixed Patent Terms Distort Innovation? Evidence from Cancer Clinical Trials

Patents award innovators a fixed period of market exclusivity, e.g., 20 years in the United States. Yet, since in many industries firms file patents at the time of discovery (“invention”) rather than first sale (“commercialization”), effective patent terms vary: inventions that commercialize at the time of invention receive a full patent term, whereas inventions that have a long time lag between invention and commercialization receive substantially reduced - or in extreme cases, zero - effective patent terms. We present a simple model formalizing how this variation may distort research and development (R&D). We then explore this distortion empirically in the context of cancer R&D, where clinical trials are shorter - and hence, effective patent terms longer - for drugs targeting late-stage cancer patients, relative to drugs targeting early-stage cancer patients or cancer prevention. Using a newly constructed data set on cancer clinical trial investments, we provide several sources of evidence consistent with fixed patent terms distorting cancer R&D. Back-of-the-envelope calculations suggest that the number of life-years at stake is large. We discuss three specific policy levers that could eliminate this distortion - patent design, targeted R&D subsidies, and surrogate (non-mortality) clinical trial endpoints - and provide empirical evidence that surrogate endpoints can be effective in practice

Patents and Research Investments: Assessing the Empirical Evidence

A well-developed theoretical literature--dating back at least to Nordhaus (1969)--has analyzed optimal patent policy design. We re-present the core trade-off of the Nordhaus model and highlight an empirical question which emerges from the Nordhaus framework as a key input into optimal patent policy design: namely, what is the elasticity of R&D investment with respect to the patent term? We then review the--surprisingly small--body of empirical evidence that has been developed on this question over the nearly half century since the publication of Nordhaus's book.National Institute on AgingNational Institutes of Health (U.S.) (Common Fund, Office of the NIH Director, through grant U01-AG046708

Do Firms Underinvest in Long-Term Research? Evidence from Cancer Clinical Trials

We investigate whether private research investments are distorted away from long-term projects. Our theoretical model highlights two potential sources of this distortion: short-termism and the fixed patent term. Our empirical context is cancer research, where clinical trials -- and hence, project durations -- are shorter for late-stage cancer treatments relative to early-stage treatments or cancer prevention. Using newly constructed data, we document several sources of evidence that together show private research investments are distorted away from long-term projects. The value of life-years at stake appears large. We analyze three potential policy responses: surrogate (non-mortality) clinical-trial endpoints, targeted R&D subsidies, and patent design

Equilibria in Sequential Allocation

Sequential allocation is a simple mechanism for sharing multiple indivisible items. We study strategic behavior in sequential allocation. In particular, we consider Nash dynamics, as well as the computation and Pareto optimality of pure equilibria, and Stackelberg strategies. We first demonstrate that, even for two agents, better responses can cycle. We then present a linear-time algorithm that returns a profile (which we call the "bluff profile") that is in pure Nash equilibrium. Interestingly, the outcome of the bluff profile is the same as that of the truthful profile and the profile is in pure Nash equilibrium for \emph{all} cardinal utilities consistent with the ordinal preferences. We show that the outcome of the bluff profile is Pareto optimal with respect to pairwise comparisons. In contrast, we show that an assignment may not be Pareto optimal with respect to pairwise comparisons even if it is a result of a preference profile that is in pure Nash equilibrium for all utilities consistent with ordinal preferences. Finally, we present a dynamic program to compute an optimal Stackelberg strategy for two agents, where the second agent has a constant number of distinct values for the items

Practical algorithms and experimentally validated incentives for equilibrium-based fair division (A-CEEI)

Approximate Competitive Equilibrium from Equal Incomes (A-CEEI) is an equilibrium-based solution concept for fair division of discrete items to agents with combinatorial demands. In theory, it is known that in asymptotically large markets: 1. For incentives, the A-CEEI mechanism is Envy-Free-but-for-Tie-Breaking (EF-TB), which implies that it is Strategyproof-in-the-Large (SP-L). 2. From a computational perspective, computing the equilibrium solution is unfortunately a computationally intractable problem (in the worst-case, assuming $\textsf{PPAD}\ne \textsf{FP}$). We develop a new heuristic algorithm that outperforms the previous state-of-the-art by multiple orders of magnitude. This new, faster algorithm lets us perform experiments on real-world inputs for the first time. We discover that with real-world preferences, even in a realistic implementation that satisfies the EF-TB and SP-L properties, agents may have surprisingly simple and plausible deviations from truthful reporting of preferences. To this end, we propose a novel strengthening of EF-TB, which dramatically reduces the potential for strategic deviations from truthful reporting in our experiments. A (variant of) our algorithm is now in production: on real course allocation problems it is much faster, has zero clearing error, and has stronger incentive properties than the prior state-of-the-art implementation.Comment: To appear in EC 202

The Core of the Participatory Budgeting Problem

In participatory budgeting, communities collectively decide on the allocation of public tax dollars for local public projects. In this work, we consider the question of fairly aggregating the preferences of community members to determine an allocation of funds to projects. This problem is different from standard fair resource allocation because of public goods: The allocated goods benefit all users simultaneously. Fairness is crucial in participatory decision making, since generating equitable outcomes is an important goal of these processes. We argue that the classic game theoretic notion of core captures fairness in the setting. To compute the core, we first develop a novel characterization of a public goods market equilibrium called the Lindahl equilibrium, which is always a core solution. We then provide the first (to our knowledge) polynomial time algorithm for computing such an equilibrium for a broad set of utility functions; our algorithm also generalizes (in a non-trivial way) the well-known concept of proportional fairness. We use our theoretical insights to perform experiments on real participatory budgeting voting data. We empirically show that the core can be efficiently computed for utility functions that naturally model our practical setting, and examine the relation of the core with the familiar welfare objective. Finally, we address concerns of incentives and mechanism design by developing a randomized approximately dominant-strategy truthful mechanism building on the exponential mechanism from differential privacy