Act Out, Get Out? Considering the Impact of School Discipline Practices in Massachusetts

Recently, testimony from three public hearings in Massachusetts suggested that excessive disciplinary action for non-violent offenses, such as tardiness and truancy, exacerbates the dropout crisis. Testimony indicated that students already behind in school are often forced to miss additional days through suspensions, which leads to a loss of credits and an inability to catch up. Some parents, educators, education stakeholders, and coalitions, including the Massachusetts Graduation and Dropout Prevention and Recovery Commission, have called for a closer look at school discipline policies and practice. Many observers have come to believe that fully understanding the role of discipline is an essential step in tackling the problem of why some Massachusetts students are not staying in school. It is within this context that the Rennie Center for Education Research & Policy embarked upon its examination of school discipline in Massachusetts.Act Out, Get Out? Considering the Impact of School Discipline Practices in Massachusetts reviews why discipline policies are necessary, laws governing these policies, and national research on the effects of disciplinary removal. The brief then describes overall trends in the disciplinary removal (suspensions and expulsions) of Massachusetts public school students over time (school year 2005-2006 through 2008-2009) and findings from a more in-depth analysis of discipline data from the 2007-2008 school year. Key findings from data about the 2007-2008 school year include: 1. For the most serious infractions, those involving illegal substances, violence and criminal activities the most common reason for disciplinary removal is violence; 2. Out-of-school suspension is the most frequently used form of disciplinary removal; 3. The number of disciplinary removals peaks at 9th grade and declines in 10th through 12th grade; 4. Particular segments (low-income, special education, male, black, Hispanic) of the student population are removed at disproportionately high rates.This policy brief highlights essential questions that need to be answered in order to fully understand how discipline policies are being carried out and to tease out the relationship between disciplinary removal, the achievement gap, and dropping out of public schools in Massachusetts. The final section of the brief puts forth considerations for policymakers and K-12 school and district leaders. The brief suggests there is a need for more detailed and complete record keeping of school discipline data as well as for more schools and districts to implement school-wide preventative approaches and alternative education programs for students who have been removed. The brief also questions the extent to which of out-of-school suspensions are used for non-violent, non-criminal offenses, particularly those for Pre-Kindergarten and Elementary School aged students.The brief was the subject of discussion at a public event on May 26, 2010

Get In… Get Out… and Stay Out Maintenance of Traffic & PCCP

Maintenance of traffic (MOT) is an important consideration for all infrastructure improvements, whether in urban, suburban, or rural scenarios. Safety for motorists, pedestrians, and workers is of paramount importance. This session will provide examples of how to best handle MOT while ensuring safety, quality, and more durable improvements to your road network

Why U.S. corporations should get out of South Africa

Paper based on a panel presentation to African Studies Association meeting Nov. 3 1978

Will They Come? Get Out The Word About Going Mobile

To be effective, libraries must promote, market, and advertise mobile initiatives. When libraries introduce services that use new tools and modes of thought, they must demonstrate what is possible, how services are relevant, and how new resources can help

Using Bayes to get the most out of non-significant results

No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors allow theory to be linked to data in a way that overcomes the weaknesses of the other approaches. Specifically, Bayes factors use the data themselves to determine their sensitivity in distinguishing theories (unlike power), and they make use of those aspects of a theory’s predictions that are often easiest to specify (unlike power and intervals, which require specifying the minimal interesting value in order to address theory). Bayes factors provide a coherent approach to determining whether non-significant results support a null hypothesis over a theory, or whether the data are just insensitive. They allow accepting and rejecting the null hypothesis to be put on an equal footing. Concrete examples are provided to indicate the range of application of a simple online Bayes calculator, which reveal both the strengths and weaknesses of Bayes factors

Get Out of the Valley: Power-Efficient Address Mapping for GPUs

GPU memory systems adopt a multi-dimensional hardware structure to provide the bandwidth necessary to support 100s to 1000s of concurrent threads. On the software side, GPU-compute workloads also use multi-dimensional structures to organize the threads. We observe that these structures can combine unfavorably and create significant resource imbalance in the memory subsystem causing low performance and poor power-efficiency. The key issue is that it is highly application-dependent which memory address bits exhibit high variability. To solve this problem, we first provide an entropy analysis approach tailored for the highly concurrent memory request behavior in GPU-compute workloads. Our window-based entropy metric captures the information content of each address bit of the memory requests that are likely to co-exist in the memory system at runtime. Using this metric, we find that GPU-compute workloads exhibit entropy valleys distributed throughout the lower order address bits. This indicates that efficient GPU-address mapping schemes need to harvest entropy from broad address-bit ranges and concentrate the entropy into the bits used for channel and bank selection in the memory subsystem. This insight leads us to propose the Page Address Entropy (PAE) mapping scheme which concentrates the entropy of the row, channel and bank bits of the input address into the bank and channel bits of the output address. PAE maps straightforwardly to hardware and can be implemented with a tree of XOR-gates. PAE improves performance by 1.31 x and power-efficiency by 1.25 x compared to state-of-the-art permutation-based address mapping