Outdoor education and feminism: a review of the outdoor adventures program at the University of Alaska Fairbanks

Master's Project (M.A.) University of Alaska Fairbanks, 2019This report is an organizational review of the Outdoor Adventures (OA) Program at the University of Alaska Fairbanks (UAF). I will be reviewing the communication strategies within the program as well as the risk mitigation and socialization process of the organization. The goal of this document is to provide a theoretical background to justify decision making and communication practices within the organization based on a feminist critical perspective. This document provides recommendations based upon improving communication dynamics that play a role in the gender disparity as well as the processes through which staff of the organization are socialized. This document provides a brief history of the OA program at UAF and a strengths, weaknesses, opportunities, threats (SWOT) analysis to give perspective on the current state of the program. Next this project contains an overview of the gender disparity in the outdoor field, ways in which risk management is viewed and implemented, and the socialization processes of staff members within the program. Methods used to review the organization included document review, direct observation, and autoethnographic practices. The results of this project include documents to aid in socialization and risk management processes and further explores recommendations to mitigate the gender gap, update risk management practices, and train staff

Management and Storage of Surface Waters Technical Staff Report

Legal documents related to a dispute between the Sawmill Slough Conservation Club vs. the University of North Floridahttps://digitalcommons.unf.edu/sawmill_history/1035/thumbnail.jp

Understanding Productivity Changes in Public Universities: Evidence from Spain

This paper describes the dynamic changes in productivity in Spanish public universities (SPU) in the period 1994 to 2008. The Malmquist index is used to illustrate the contribution of efficiency and technological change to changes in the productivity of university activities. The results indicate that annual productivity growth is attributable more to efficiency improvements than technological progress. Gains in scale efficiency appear to play only a minor role in productivity gains. The fact that technical efficiency contributes more than technological progress suggests that most universities are not operating close to the best-practice frontier.Garcia Aracil, A. (2013). Understanding Productivity Changes in Public Universities: Evidence from Spain. Research Evaluation. 22(5):351-368. doi:10.1093/reseval/rvt009S351368225Agasisti, T., Catalano, G., Landoni, P., & Verganti, R. (2012). Evaluating the performance of academic departments: an analysis of research-related output efficiency. Research Evaluation, 21(1), 2-14. doi:10.1093/reseval/rvr001Agasisti, T., & Pérez-Esparrells, C. (2009). Comparing efficiency in a cross-country perspective: the case of Italian and Spanish state universities. Higher Education, 59(1), 85-103. doi:10.1007/s10734-009-9235-8ARCELUS‡, F. J., & Coleman‡§, D. F. (1997). An efficiency review of university departments. International Journal of Systems Science, 28(7), 721-729. doi:10.1080/00207729708929431Athanassopoulos, A. D., & Shale, E. (1997). Assessing the Comparative Efficiency of Higher Education Institutions in the UK by the Means of Data Envelopment Analysis. Education Economics, 5(2), 117-134. doi:10.1080/09645299700000011Attewell, P., Heil, S., & Reisel, L. (2012). What Is Academic Momentum? And Does It Matter? Educational Evaluation and Policy Analysis, 34(1), 27-44. doi:10.3102/0162373711421958Balk, B. M. (1993). Malmquist Productivity Indexes and Fisher Ideal Indexes: Comment. The Economic Journal, 103(418), 680. doi:10.2307/2234540Beasley, J. E. (1990). Comparing university departments. Omega, 18(2), 171-183. doi:10.1016/0305-0483(90)90064-gBeasley, J. E. (1995). Determining Teaching and Research Efficiencies. Journal of the Operational Research Society, 46(4), 441-452. doi:10.1057/jors.1995.63Bessent, A. M., & Bessent, E. W. (1980). Determining the Comparative Efficiency of Schools through Data Envelopment Analysis. Educational Administration Quarterly, 16(2), 57-75. doi:10.1177/0013161x8001600207Bonaccorsi, A., Daraio, C., & Simar, L. (2006). Advanced indicators of productivity of universitiesAn application of robust nonparametric methods to Italian data. Scientometrics, 66(2), 389-410. doi:10.1007/s11192-006-0028-xBonaccorsi, A., Daraio, C., Lepori, B., & Slipersæter, S. (2007). Indicators on individual higher education institutions: addressing data problems and comparability issues. Research Evaluation, 16(2), 66-78. doi:10.3152/095820207x218141Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity. Econometrica, 50(6), 1393. doi:10.2307/1913388Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. doi:10.1016/0377-2217(78)90138-8Coelli, T., & Perelman, S. (1999). A comparison of parametric and non-parametric distance functions: With application to European railways. European Journal of Operational Research, 117(2), 326-339. doi:10.1016/s0377-2217(98)00271-9Cohn, E., Rhine, S. L. W., & Santos, M. C. (1989). Institutions of Higher Education as Multi-Product Firms: Economies of Scale and Scope. The Review of Economics and Statistics, 71(2), 284. doi:10.2307/1926974COSTAS, R., & BORDONS, M. (2007). The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level. Journal of Informetrics, 1(3), 193-203. doi:10.1016/j.joi.2007.02.001De Groot, H., McMahon, W. W., & Volkwein, J. F. (1991). The Cost Structure of American Research Universities. The Review of Economics and Statistics, 73(3), 424. doi:10.2307/2109566F�re, R., Grosskopf, S., & Lovell, C. A. K. (1992). Indirect productivity measurement. Journal of Productivity Analysis, 2(4), 283-298. doi:10.1007/bf00156471Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253. doi:10.2307/2343100Flegg, A. T., & Allen, D. O. (2007). Does Expansion Cause Congestion? The Case of the Older British Universities, 1994–2004. Education Economics, 15(1), 75-102. doi:10.1080/09645290601133928FLEGG, A. T., ALLEN, D. O., FIELD, K., & THURLOW, T. W. (2004). Measuring the efficiency of British universities: a multi‐period data envelopment analysis. Education Economics, 12(3), 231-249. doi:10.1080/0904529042000258590García-Aracil, A., & Palomares-Montero, D. (2009). Examining benchmark indicator systems for the evaluation of higher education institutions. Higher Education, 60(2), 217-234. doi:10.1007/s10734-009-9296-8García-Aracil, A., & Palomares-Montero, D. (2012). Indicadores para la evaluación de las instituciones universitarias: validación a través del método Delphi. Revista española de Documentación Científica, 35(1), 119-144. doi:10.3989/redc.2012.1.863Giménez, V. M., & Martínez, J. L. (2006). Cost efficiency in the university: A departmental evaluation model. Economics of Education Review, 25(5), 543-553. doi:10.1016/j.econedurev.2005.05.006Glass, J. C., McKillop, D. G., & O’Rourke, G. (1998). Journal of Productivity Analysis, 10(2), 153-175. doi:10.1023/a:1018607223276Grifell-Tatjé, E., & Lovell, C. A. K. (1999). A generalized Malmquist productivity index. Top, 7(1), 81-101. doi:10.1007/bf02564713Grosskopf, S., Margaritis, D., & Valdmanis, V. (1995). Estimating output substitutability of hospital services: A distance function approach. European Journal of Operational Research, 80(3), 575-587. doi:10.1016/0377-2217(94)00138-3Jiménez-Contreras, E., de Moya Anegón, F., & López-Cózar, E. D. (2003). The evolution of research activity in Spain. Research Policy, 32(1), 123-142. doi:10.1016/s0048-7333(02)00008-2Johnes, G. (1988). Determinants of research output in economics departments in British universities. Research Policy, 17(3), 171-178. doi:10.1016/0048-7333(88)90041-8JOHNES, J. (2008). EFFICIENCY AND PRODUCTIVITY CHANGE IN THE ENGLISH HIGHER EDUCATION SECTOR FROM 1996/97 TO 2004/5*. Manchester School, 76(6), 653-674. doi:10.1111/j.1467-9957.2008.01087.xJohnes, G., & Schwarzenberger, A. (2011). Differences in cost structure and the evaluation of efficiency: the case of German universities. Education Economics, 19(5), 487-499. doi:10.1080/09645291003726442JOHNES, J., & YU, L. (2008). Measuring the research performance of Chinese higher education institutions using data envelopment analysis. China Economic Review, 19(4), 679-696. doi:10.1016/j.chieco.2008.08.004Koshal, R. K., & Koshal, M. (1999). Economies of scale and scope in higher education: a case of comprehensive universities. Economics of Education Review, 18(2), 269-277. doi:10.1016/s0272-7757(98)00035-1Kortelainen, M. (2008). Dynamic environmental performance analysis: A Malmquist index approach. Ecological Economics, 64(4), 701-715. doi:10.1016/j.ecolecon.2007.08.001Laudel, G. (2005). Is external research funding a valid indicator for research performance? Research Evaluation, 14(1), 27-34. doi:10.3152/147154405781776300Lovell, C. A. K. (2003). Journal of Productivity Analysis, 20(3), 437-458. doi:10.1023/a:1027312102834Lucas, S. R., & Beresford, L. (2010). Naming and Classifying: Theory, Evidence, and Equity in Education. Review of Research in Education, 34(1), 25-84. doi:10.3102/0091732x09353578Madden, G., Savage, S., & Kemp, S. (1997). Measuring Public Sector Efficiency: A Study of Economics Departments at Australian Universities. Education Economics, 5(2), 153-168. doi:10.1080/09645299700000013Abbott, M., & Doucouliagos, C. (2001). Total factor productivity and efficiency in Australian colleges of advanced education. Journal of Educational Administration, 39(4), 384-393. doi:10.1108/eum0000000005497Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estadistica, 4(2), 209-242. doi:10.1007/bf03006863Mamun, S. A. K. (2012). Stochastic estimation of cost frontier: evidence from Bangladesh. Education Economics, 20(2), 211-227. doi:10.1080/09645292.2010.494836Maniadakis, N., & Thanassoulis, E. (2004). A cost Malmquist productivity index. European Journal of Operational Research, 154(2), 396-409. doi:10.1016/s0377-2217(03)00177-2Molinero, C. M. (1996). On the Joint Determination of Efficiencies in a Data Envelopment Analysis Context. Journal of the Operational Research Society, 47(10), 1273-1279. doi:10.1057/jors.1996.154Molinero, C. M., & Tsai, P. F. (1997). Some mathematical properties of a DEA model for the joint determination of efficiencies. Journal of the Operational Research Society, 48(1), 51-56. doi:10.1057/palgrave.jors.2600327McLendon, M. K., Hearn, J. C., & Deaton, R. (2006). Called to Account: Analyzing the Origins and Spread of State Performance-Accountability Policies for Higher Education. Educational Evaluation and Policy Analysis, 28(1), 1-24. doi:10.3102/01623737028001001Monk, D. H. (1992). Education Productivity Research: An Update and Assessment of Its Role in Education Finance Reform. Educational Evaluation and Policy Analysis, 14(4), 307-332. doi:10.3102/01623737014004307Nishimizu, M., & Page, J. M. (1982). Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, 1965-78. The Economic Journal, 92(368), 920. doi:10.2307/2232675Rodrı́guez-Álvarez, A., Fernández-Blanco, V., & Lovell, C. A. K. (2004). Allocative inefficiency and its cost: International Journal of Production Economics, 92(2), 99-111. doi:10.1016/j.ijpe.2003.08.012Salerno, C. (2006). Using Data Envelopment Analysis to Improve Estimates of Higher Education Institution’s Per‐student Education Costs1. Education Economics, 14(3), 281-295. doi:10.1080/09645290600777485Sarafoglou, N., & Haynes, K. E. (1996). University productivity in Sweden: a demonstration and explanatory analysis for economics and business programs. The Annals of Regional Science, 30(3), 285-304. doi:10.1007/bf01580523Schmoch, U., Schubert, T., Jansen, D., Heidler, R., & von Görtz, R. (2010). How to use indicators to measure scientific performance: a balanced approach. 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The Hyper-X Flight Systems Validation Program

For the Hyper-X/X-43A program, the development of a comprehensive validation test plan played an integral part in the success of the mission. The goal was to demonstrate hypersonic propulsion technologies by flight testing an airframe-integrated scramjet engine. Preparation for flight involved both verification and validation testing. By definition, verification is the process of assuring that the product meets design requirements; whereas validation is the process of assuring that the design meets mission requirements for the intended environment. This report presents an overview of the program with emphasis on the validation efforts. It includes topics such as hardware-in-the-loop, failure modes and effects, aircraft-in-the-loop, plugs-out, power characterization, antenna pattern, integration, combined systems, captive carry, and flight testing. Where applicable, test results are also discussed. The report provides a brief description of the flight systems onboard the X-43A research vehicle and an introduction to the ground support equipment required to execute the validation plan. The intent is to provide validation concepts that are applicable to current, follow-on, and next generation vehicles that share the hybrid spacecraft and aircraft characteristics of the Hyper-X vehicle