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Policy Research
Opiate treatment in the criminal justice system: a review of crimesolutions.gov evidence rated programs
J. Mitchell Miller, O. Hayden Griffin III, Courtney Marciá Gardner
This article examines the national effort to treat drug offenders and disrupt drug crime trajectories via treatment initiatives regarding opiate abuse. Funding for program implementation is driven by the efficacy of proposed recovery strategies as increasingly represented by the inclusion of established evidence based practices and treatment. This article looks at the role of Medicated Assisted Treatment (MAT) for opiate addiction and provides an analysis of opiate treatment programs designated as effective or promising in a national evidence based registry. This article finds scant evidence for rated opiate treatment programs listed in crimesolutions.gov. The authors find that there is an absence of implementation and process evaluation components that demonstrate efficacy for opiate treatment programs within the criminal justice system.
Government and Market Pathologies of Privatization: The Case of Prison Privatization
John C. Morris
This article argues that the privatization of correctional facilities is best understood as a combination of government failures, market failures, and political incentives. It deploys a case-study approach to examine prison privatization in Mississippi, the article concludes that prison privatization not only fails to correct certain government or market failures, but also creates additional ‘hybrid’ pathologies that combine elements of both government and market failures. This article offers an alternative method of analysis for privatized arrangements by looking at market pathologies that effect the privatization arrangement.
Alternative rebate rules in the provision of a threshold public good: An experimental investigation
Melanie Marks, Rachel Croson
This article summarizes the authors’ research on the effects of rebate rules on voluntary contributions to threshold public goods. In their research, the authors examined three separate rebate rules and their effects on voluntary contributions from a group of participants. The three rebate rules that were examined were the No Rebate policy where any excess contributions are not given back to the contributors, the Proportional Rebate policy where rebates are given back to the contributors in proportion to how much they originally gave, and the Utilization Rebate policy where no rebate is given and the excess contributions are used on future public goods. To translate this into a real life situation, the authors used a 1995 situation where a company in New York needed funds for an environmentally friendly energy project. Citizens in New York could opt into the program, and an extra fee would be added to their electricity bill. If a No Rebate policy would be implemented in this situation, any extra funds the company had after project would be wasted. This could mean that they are kept by the company, or used for office needs. No money would be returned to the contributors. If a Proportional Rebate policy was in place, the excess contributions would be given back to the citizens in the proportion that they contributed to the project. If there was a Utilization Rebate policy in place, the company would take the excess contributions and use it toward another public good, like planting trees. No Rebate policies have the highest penalty for contribution, as the individual’s excess contribution is wasted, while the Utilization Rebate policy has the least amount of penalty for contributing because any excess contributions are put towards more public goods that benefit the contributors. The researchers found that the amount of contributions is directly correlated to what penalties come with over contribution. The highest amount of contribution was seen when the Utilization Rebate treatment was in place, and the least amount when the No Rebate policy treatment was in place.
Quantifying Trading Behavior in Financial Markets Using Google Trends
Tobias Preis, Helen Susannah Moat, H. Eugene Stanley
The authors used google trend data, which “provides access to aggregated information on the volume of queries for different search terms and how these volumes change over time” to examine the relationship between this big data source, and the stock market. The authors used a complex statistical model to examine the relationship between particular search terms, and stock market movements. They found that google trends not only accurately predicted the current state of the market, but also provided insight into future stock market movement as well. Essentially, the authors selected certain financial terms, such as ‘debt’, and examined the search volume relative to particular trends in the market. They found that these search terms were more highly searched for preceding a market movement. Further, the authors used these search terms, and their predicted impact of the movements on the market to create a successful future trading strategy that would have been quite profitable if implemented.
Quantifying the Advantage of Looking Forward
Tobias Preis, Helen Susannah Moat, H. Eugene Stanley, Steven R. Bishop
The authors used google search logs to compare across country results for google searches. By using the roman numerals for years, which are ubiquitous across countries, the authors, for the first time, were able to use google trend data to compare data across countries, as opposed to comparison of terms in particular regions. The authors then used statistical methods to compare the rate at which countries searched for past dates, and future dates, and the correlation with GDP for that particular country. The authors found a statistically significant result that showed a strong correlation between searching for future years and growth within a country’s GDP, i.e. countries that search for future years have a stronger growth in GDP when compared to countries that search for previous years.
Detecting influenza epidemics using search engine query data
Jeremy Ginsberg, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski, Larry Brilliant
The authors used an early version of google trends, which shows what people are searching for on google in a particular region; to measure where/when people had the flu. They then converted this data into a real time, region specific, data detection method, essentially attempting to see where and when people were searching for issues related to having the flu. Essentially, the authors were attempting to use google trends to predict where the flu was occurring. And they found a high correlation between people searching for flu-related terms, and actual physician visits related to having the flu. This model, the author’s claimed, successfully reported areas where the flu was prevalent in as little as one day, much sooner than the estimates provided by the CDC which averaged at least two weeks.
Policy image resilience, multidimensionality, and policy image management: a study of US biofuel policy
Renee O’Connell
The authors provide a history of the rise of biofuels in the US and use the work of political scientists such as Baumgartner and Jones to explain why attacks by powerful interests such as the oil industry, food producers, and those fighting hunger had little negative impact on the production of biofuels and government policies that promote biofuels. Opponents of biofuels rallied behind the catchy “food before fuel” slogan, but the biofuels advocacy coalition was able to react cohesively and develop a central message that logically blamed the oil industry and food producers for the spike in food prices. The authors go beyond the simple argument posited by political equilibrium theory that those fighting biofuels were not successful not only because of failed venue shopping but also argue that biofuel opponents failed for three other reasons: the congruence of the biofuel policy image with core values and current national concerns, the multidimensionality of the policy image, and the policy image management strategies of biofuel supporters.
Prison Privatization: A Meta analysis of Cost and Quality of Confinement Indicators
Brad W. Lundahl, Chelsea Kunz, Cyndi Brownell, Norma Harris, Russ Van Vleet
This article examines the results of prison privatization and seeks to provide an empirical base from which decisions about privatization might be made. The authors conducted a meta-analysis of reports on comparisons between privately managed and publicly managed prisons. Indicators of cost and quality of confinement were assessed and the results suggest that privately managed prisons provide no clear benefit or detriment to the system. The article finds that cost savings from privatizing prisons are not guaranteed and are minimal and that quality of confinement is similar across privately and publically managed systems, with public prisons delivering slightly better skills training to inmates and have fewer inmate grievances than private prisons.
Where Have All the (White and Hispanic) Inmates Gone? Comparing the Racial Composition of Private and Public Adult Correctional Facilities
Brett C. Burkhardt
This article examines racial disparities in imprisonment rates to consider racial disparities in inmate populations across privately operated and publicly operated correctional facilities. The study reveals that in 2005, White inmates were significantly underrepresented and Hispanics significantly overrepresented in private correctional facilities relative to public ones. Results from multilevel models show that being privately operated decreased the White share of a facility’s population by more than eight percentage points and increased the Hispanic share of a facility’s population by nearly two percentage points. Mounting evidence suggests that private correctional facilities lag their public counterparts in a number of ways that influence inmates’ conditions of confinement. These findings raise legal questions about equal protection of inmates and economic questions about the reliance of private correctional firms on Hispanic inmates.
Michigans RPS ballot defeat: A policy failure or success?
Fei Li, Barry D. Solomon, Adam M. Wellstead
This article examines what constitutes a policy failure and how policy failure can be evaluated by looking at the 2012 failure of Proposal 3, which was a constitutional amendment that would have mandated that 25% of the State’s electricity must come from renewable resources by 2015. Specifically, through implementation of a renewable portfolio standard (RPS), Proposal 3 would have required energy suppliers generate a certain amount of electricity from qualified renewable energy sources. The article provides background to Michigan’s existing RPS, presents an ex-ante cost-benefit evaluation of the defeated RPS proposal, and determines that RPS can fail in four key ways.