15 research outputs found

    Alaska Energy Statistics 1960‐2009

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    This report has had various publishers. Before 1985, the federal Alaska Power Administration published Alaska Electric Power Statistics. Then, the Alaska Energy Authority (formerly the Alaska Power Authority) began gathering statistical data and publishing this annual report. In 1988, the Alaska Electric Power Statistics report became a combined effort of the Alaska Systems Coordinating Council and the Alaska Energy Authority. Beginning in 1993, the report became a joint effort of the Alaska Systems Coordinating Council and the Alaska Department of Community and Regional Affairs, Division of Energy. After the 1995 report, no reports were issued until 2003, when the Institute of Social and Economic Research (ISER) at the University of Alaska Anchorage (UAA), published a report, with funding from the Alaska Energy Authority (AEA), the Regulatory Commission of Alaska (RCA), and the Denali Commission. ISER prepared this twenty‐fourth edition of the Alaska Electric Energy Statistics in collaboration with the Alaska Energy Authority. Unlike previous reports, data tables are presented solely in digital form in an MS Excel file. The workbook containing the data tables is available on the ISER website at http://iser.uaa.alaska.edu/Publications/AlaskaEnergyStatisticsCY2009Tables.xlsx) and the AEA website (http://www.akenergyauthority.org/).The data tables are presented in a dataset format for convenient use and manipulation. All data presented are identified by the geographic regions used in previous Alaska Electric Energy Statistics,1 as well as AEA energy regions, Alaska Native corporation regions, and census areas.Alaska Energy Authority.Introduction / Summary and Highlight

    Alaska Energy Statistics 1960-2010 Final Report

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    Prior to 1985, the federal Alaska Power Administration published the Alaska Electric Power Statistics. Then, the Alaska Energy Authority (formerly the Alaska Power Authority) began gathering statistical data and publishing this annual report. In 1988, the Alaska Electric Power Statistics report became a combined effort between the Alaska Systems Coordinating Council and the Alaska Energy Authority. Beginning in 1993, the report became a joint effort between the Alaska Systems Coordinating Council and the Alaska Department of Community and Regional Affairs, Division of Energy. After the 1995 report, no further reports were published until 2003 when a report was prepared by the Institute of Social and Economic Research (ISER), University of Alaska Anchorage (UAA), with funding provided by the Alaska Energy Authority (AEA), the Regulatory Commission of Alaska (RCA), and the Denali Commission.The purpose of this report is to present electric power reference data for Alaska; it is not intended to provide detailed analysis of energy production, consumption or uses.Alaska Energy Authority.Introduction / Summary and Highlight

    Administrative Burden in Federal Student Loan Repayment, and Socially Stratified Access to Income-Driven Repayment Plans

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    This study considers socially stratified take-up of income-driven repayment plans among federal student loan borrowers with high-debt payment obligations. Qualitative analyses of borrower complaints from the Consumer Financial Protection Bureau are used to document borrowers’ experiences of administrative burden in the federal loan repayment system. The combined effects of burdens on access to payment relief programs are quantified using both administrative data from a national sample of consumer credit reports and restricted-use survey data from the Beginning Postsecondary Longitudinal Study (BPS). Socioeconomic and racial gaps in take-up of income-driven repayment (IDR) plans are estimated among the subset of borrowers who would face high loan payment-to-income ratios under a standard repayment plan. Regression models indicate that among these borrowers, those living in lower-income census blocks are less likely to be enrolled in IDR

    Predation in Online Degree Programs: An Institutional Analysis

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    Widespread fraud and adverse student outcomes in the expansion of online for-profit colleges raise urgent questions about the new surge in online programs. These questions also extend to public and private non-profit colleges, which often employ for-profit contractors or partners to run large parts of their online degree programs. In this study, we will investigate how colleges’ prevalence of online education associates with student body demographics, retention and debt outcomes, and leading indicators of predatory practice. Crucially, our analyses will include not only for-profit colleges with online programs, but also the growing number of public and private non-profit colleges that offer such programs. The analyses will yield important evidence on the extent of predation in the new landscape of online higher education

    Student debt, Need-based aid formulas, and the Racial Wealth Gap

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    An analysis of relationships between student debt, need-based financial aid formulas, and the racial wealth ga

    The Effect of Radiation Therapy on Cancer Patients Participating in Structured Exercise

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    Radiation therapy was first attempted as a treatment for cancer in 1896. Since then, it has become a common modality, and the survival rate among diagnosed patients has increased drastically. While radiation can prolong life expectancy, it can be deleterious to the patients’ health. Exercise has consistently demonstrated improvement in anthropometric, cardiometabolic, and functional capacities of cancer survivors, but data concerning the effect of radiation on exercise outcomes are limited. PURPOSE: To evaluate the effect of radiation therapy on exercise outcomes in cancer survivors. METHODS: Patients participated in a 10-week exercise intervention involving aerobic, resistance, and flexibility training. There were 59 patients who had never used radiation (NR), 63 who had complete radiotherapy (HR), 18 currently undergoing treatment (CR),and 17 who failed to report their status. We analyzed differences among the three radiation exposure groups (NR, HR, and CR) in baseline characteristics, exercise adherence, and improvement in several parameters of health and function using chi-square and multivariate tests; post-hoc analyses tested specific group differences. RESULTS: There were no baseline differences between groups in age, health history, body composition, cardiovascular parameters, fatigue, insomnia, or depression. Patients in the NR group performed better on the five times sit-to-stand test than HR patients (p=0.013) and better on sit-and-reach (p=0.037) and functional reach (p=0.059) than CR patients. There were no differences in program completion based on use of radiation (p=0.404). Although there were no baseline differences in the six-minute walk (p=0.987), CR patients improved more than HR patients (p=0.038) and NR patients (p=0.051). There were no baseline differences in systolic blood pressure (p=0.957) but CR patients experienced greater reductions than patients in the HR group (p=0.011) and NR group (p=0.035). CONCLUSION: Exercise may be an effective way to mitigate some of the health consequences associated with radiation therapy. In our sample, exercise improved blood pressure and six minute walk more in patients who were currently undergoing treatment; however, our low retention rate may create potential bias and fail to accurately characterize expected results
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