Credibility and Policy Convergence: Evidence from U.S. House Roll Call Voting Records

Traditional models of politician behavior predict complete or partial policy convergence, whereby electoral competition compels partisan politicians to choose positions more moderate than their most-preferred policies. Alternatively, if politicians cannot overcome the inability to make binding pre-commitments to policies, the expected result is complete policy divergence. By exploiting a regression discontinuity (RD) design inherent in the Congressional electoral system, this paper empirically tests the strong predictions of the complete divergence hypothesis against the alternative of partial convergence within the context of Representatives' roll call voting behavior in the U.S. House (1946-1994). The RD design implies that which party wins a district seat is quasi-randomly assigned among elections that turn out to be 'close'. We use this variation to examine if Representatives' roll call voting patterns do not respond to large exogenous changes in the probability of winning the election, the strong prediction of complete policy divergence. The evidence is more consistent with full divergence and less consistent with partial convergence, suggestive that the difficulty of establishing credible commitments to policies is an important real-world phenomenon.

Addressing LISA Science Analysis Challenges

The principal goal of the \emph{LISA Science Analysis Workshop} is to encourage the development and maturation of science analysis technology in preparation for LISA science operations. Exactly because LISA is a pathfinder for a new scientific discipline -- gravitational wave astronomy -- LISA data processing and science analysis methodologies are in their infancy and require considerable maturation if they are to be ready to take advantage of LISA data. Here we offer some thoughts, in anticipation of the LISA Science Analysis Workshop, on analysis research problems that demonstrate the capabilities of different proposed analysis methodologies and, simultaneously, help to push those techniques toward greater maturity. Particular emphasis is placed on formulating questions that can be turned into well-posed problems involving tests run on specific data sets, which can be shared among different groups to enable the comparison of techniques on a well-defined platform.Comment: 7 page

The Testbed for LISA Analysis Project

The Testbed for LISA Analysis (TLA) Project aims to facilitate the development, validation and comparison of different methods for LISA science data analysis, by the broad LISA Science Community, to meet the special challenges that LISA poses. It includes a well-defined Simulated LISA Data Product (SLDP), which provides a clean interface between the communities that have developed to model and to analyze the LISA science data stream; a web-based clearinghouse (at ) providing SLDP software libraries, relevant software, papers and other documentation, and a repository for SLDP data sets; a set of mailing lists for communication between and among LISA simulators and LISA science analysts; a problem tracking system for SLDP support; and a program of workshops to allow the burgeoning LISA science community to further refine the SLDP definition, define specific LISA science analysis challenges, and report their results. This note describes the TLA Project, the resources it provides immediately, its future plans, and invites the participation of the broader community in the furtherance of its goals.Comment: 5 pages, no figure

Protecting Time Series Data with Minimal Forecast Loss

Forecasting could be negatively impacted due to anonymization requirements in data protection legislation. To measure the potential severity of this problem, we derive theoretical bounds for the loss to forecasts from additive exponential smoothing models using protected data. Following the guidelines of anonymization from the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), we develop the $k$-nearest Time Series ($k$-nTS) Swapping and $k$-means Time Series ($k$-mTS) Shuffling methods to create protected time series data that minimizes the loss to forecasts while preventing a data intruder from detecting privacy issues. For efficient and effective decision making, we formally model an integer programming problem for a perfect matching for simultaneous data swapping in each cluster. We call it a two-party data privacy framework since our optimization model includes the utilities of a data provider and data intruder. We apply our data protection methods to thousands of time series and find that it maintains the forecasts and patterns (level, trend, and seasonality) of time series well compared to standard data protection methods suggested in legislation. Substantively, our paper addresses the challenge of protecting time series data when used for forecasting. Our findings suggest the managerial importance of incorporating the concerns of forecasters into the data protection itself

How has the Louisiana Scholarship Program Affected Students? A Comprehensive Summary of Effects after Four Years

School choice has long been a subject of robust debate. Private school vouchers—programs providing public funds for students to attend K-12 private schools—tend to be the most contentious form of school choice. Over the past three years, our research team has released a series of reports examining how the LSP has affected key student and community conditions

Selective serotonin reuptake inhibitors (SSRIs) for stroke recovery.

BACKGROUND: Stroke is the major cause of adult disability. Selective serotonin reuptake inhibitors (SSRIs) have been used for many years to manage depression. Recently, small trials have demonstrated that SSRIs might improve recovery after stroke, even in people who are not depressed. Systematic reviews and meta-analyses are the least biased way to bring together data from several trials. Given the promising effect of SSRIs on stroke recovery seen in small trials, a systematic review and meta-analysis is needed. OBJECTIVES: To determine whether SSRIs improve recovery after stroke, and whether treatment with SSRIs was associated with adverse effects. SEARCH METHODS: We searched the Cochrane Stroke Group Trials Register (August 2011), Cochrane Depression Anxiety and Neurosis Group Trials Register (November 2011), Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 8), MEDLINE (from 1948 to August 2011), EMBASE (from 1980 to August 2011), CINAHL (from 1982 to August 2011), AMED (Allied and Complementary Medicine) (from 1985 to August 2011), PsycINFO (from 1967 to August 2011) and PsycBITE (Pyschological Database for Brain Impairment Treatment Efficacy) (March 2012). To identify further published, unpublished and ongoing trials we searched trials registers, pharmaceutical websites, reference lists, contacted experts and performed citation tracking of included studies. SELECTION CRITERIA: We included randomised controlled trials that recruited stroke survivors (ischaemic or haemorrhagic) at any time within the first year. The intervention was any SSRI, given at any dose, for any period. We excluded drugs with mixed pharmacological effects. The comparator was usual care or placebo. In order to be included, trials had to collect data on at least one of our primary (dependence and disability) or secondary (impairments, depression, anxiety, quality of life, fatigue, healthcare cost, death, adverse events and leaving the trial early) outcomes. DATA COLLECTION AND ANALYSIS: We extracted data on demographics, type of stroke, time since stroke, our primary and secondary outcomes, and sources of bias. For trials in English, two review authors independently extracted data. For Chinese papers, one review author extracted data. We used standardised mean differences (SMD) to estimate treatment effects for continuous variables, and risk ratios (RR) for dichotomous effects, with their 95% confidence intervals (CIs). MAIN RESULTS: We identified 56 completed trials of SSRI versus control, of which 52 trials (4059 participants) provided data for meta-analysis. There were statistically significant benefits of SSRI on both of the primary outcomes: RR for reducing dependency at the end of treatment was 0.81 (95% CI 0.68 to 0.97) based on one trial, and for disability score, the SMD was 0.91 (95% CI 0.60 to 1.22) (22 trials involving 1343 participants) with high heterogeneity between trials (I(2) = 87%; P < 0.0001). For neurological deficit, depression and anxiety, there were statistically significant benefits of SSRIs. For neurological deficit score, the SMD was -1.00 (95% CI -1.26 to -0.75) (29 trials involving 2011 participants) with high heterogeneity between trials (I(2) = 86%; P < 0.00001). For dichotomous depression scores, the RR was 0.43 (95% CI 0.24 to 0.77) (eight trials involving 771 participants) with high heterogeneity between trials (I(2) = 77%; P < 0.0001). For continuous depression scores, the SMD was -1.91 (95% CI -2.34 to -1.48) (39 trials involving 2728 participants) with high heterogeneity between trials (I(2) = 95%; P < 0.00001). For anxiety, the SMD was -0.77 (95% CI -1.52 to -0.02) (eight trials involving 413 participants) with high heterogeneity between trials (I(2) = 92%; P < 0.00001). There was no statistically significant benefit of SSRI on cognition, death, motor deficits and leaving the trial early. For cognition, the SMD was 0.32 (95% CI -0.23 to 0.86), (seven trials involving 425 participants) with high heterogeneity between trials (I(2) = 86%; P < 0.00001). The RR for death was 0.76 (95% CI 0.34 to 1.70) (46 trials involving 3344 participants) with no heterogeneity between trials (I(2) = 0%; P = 0.85). For motor deficits, the SMD was -0.33 (95% CI -1.22 to 0.56) (two trials involving 145 participants). The RR for leaving the trial early was 1.02 (95% CI 0.86 to 1.21) in favour of control, with no heterogeneity between trials. There was a non-significant excess of seizures (RR 2.67; 95% CI 0.61 to 11.63) (seven trials involving 444 participants), a non-significant excess of gastrointestinal side effects (RR 1.90; 95% CI 0.94 to 3.85) (14 trials involving 902 participants) and a non-significant excess of bleeding (RR 1.63; 95% CI 0.20 to 13.05) (two trials involving 249 participants) in those allocated SSRIs. Data were not available on quality of life, fatigue or healthcare costs.There was no clear evidence from subgroup analyses that one SSRI was consistently superior to another, or that time since stroke or depression at baseline had a major influence on effect sizes. Sensitivity analyses suggested that effect sizes were smaller when we excluded trials at high or unclear risk of bias.Only eight trials provided data on outcomes after treatment had been completed; the effect sizes were generally in favour of SSRIs but CIs were wide. AUTHORS' CONCLUSIONS: SSRIs appeared to improve dependence, disability, neurological impairment, anxiety and depression after stroke, but there was heterogeneity between trials and methodological limitations in a substantial proportion of the trials. Large, well-designed trials are now needed to determine whether SSRIs should be given routinely to patients with stroke

Coulomb interaction signatures in self-assembled lateral quantum dot molecules

We use photoluminescence spectroscopy to investigate the ground state of single self-assembled InGaAs lateral quantum dot molecules. We apply a voltage along the growth direction that allows us to control the total charge occupancy of the quantum dot molecule. Using a combination of computational modeling and experimental analysis, we assign the observed discrete spectral lines to specific charge distributions. We explain the dynamic processes that lead to these charge configurations through electrical injection and optical generation. Our systemic analysis provides evidence of inter-dot tunneling of electrons as predicted in previous theoretical work.Comment: 9 pages, 4 figure

Connecting Inquiry and Values in Science Education: An Approach based on John Dewey’s Perspective

Science education owes a lot to John Dewey’s ideas of how science should be viewed and what science education should do. In this study, we explore how to help students use inquiry in decision-making based on John Dewey’s perspective. Science education aims for citizens to be scientifically literate, so that they can make informed-decisions in science-related issues. Conducting scientific inquiry is expected to help students make informed decisions, however, it is not clear how scientific inquiry can help decision-making in science education. Dewey suggested that scientific inquiry should include a good value judgment, and conducting the inquiry can improve the ability of value judgment. Decision-making requires value judgment, therefore Dewey’s ideas can explain how conducting inquiry can contribute to make an informed decision through value judgment. According to Dewey, each value judgment during the inquiry is a practical judgment guiding an action and involved values are represented in the consequences of the action. Thus, students can evaluate their value judgments by evaluating their actions during the scientific inquiry. Values in science have been mentioned in science education standards, but the relationship between values and inquiry has not been much explained. Based on Dewey’s perspective, we explained how to connect inquiry and values and how this connection can contribute to make informed decisions