Decreasing Opportunities for Low-Wage Workers: The Role of the Nondiscrimination Law for Employer-Provided Health Insurance

As of 1978, the favorable tax treatment of fringe benefits, including health insurance, has been regulated via a nondiscrimination clause such that low-wage, full-time workers must be offered health insurance (and other benefits) that are offered to higher-wage workers by the firm. Part-time workers may be excluded from coverage, however, creating incentives for firms to hire some types of workers part time to deny them coverage. We hypothesize that firms will hire fewer workers whose relative costs have increased, that is, low-wage workers. These workers will be less likely to work for firms that offer coverage, and those that do will be more likely to work part time without being eligible for the firm’s health insurance benefits. We use the 1988 and 1993 Employee Benefits Supplements to the Current Population Surveys and an employer premium imputation to examine these hypotheses. Both the descriptive and multivariate analysis are consistent with our hypotheses. We predict the probability of working for a firm that offers health insurance to decrease as premiums increase for both high- and low-wage workers. An increase in the premium is also associated with a decrease in the probability of part-time work, but an even greater decrease in the joint probability of part-time work with eligibility for health insurance.

Plasmas in Saturn's magnetosphere

The solar wind plasma analyzer on board Pioneer 2 provides first observations of low-energy positive ions in the magnetosphere of Saturn. Measurable intensities of ions within the energy-per-unit charge (E/Q) range 100 eV to 8 keV are present over the planetocentric radial distance range about 4 to 16 R sub S in the dayside magnetosphere. The plasmas are found to be rigidly corotating with the planet out to distances of at least 10 R sub S. At radial distances beyond 10 R sub S, the bulk flows appear to be in the corotation direction but with lesser speeds than those expected from rigid corotation. At radial distances beyond the orbit of Rhea at 8.8 R sub S, the dominant ions are most likely protons and the corresponding typical densities and temperatures are 0.5/cu cm and 1,000,000 K, respectively, with substantial fluctuations. It is concluded that the most likely source of these plasmas in the photodissociation of water frost on the surface of the ring material with subsequent ionization of the products and radially outward diffusion. The presence of this plasma torus is expected to have a large influence on the dynamics of Saturn's magnetosphere since the pressure ratio beta of these plasmas approaches unity at radial distances as close to the planet as 6.5 R sub S. On the basis of these observational evidences it is anticipated that quasi-periodic outward flows of plasma, accompanied with a reconfiguration of the magnetosphere beyond about 6.5 R sub S, will occur in the local night sector in order to relieve the plasma pressure from accretion of plasma from the rings

Feedback system for divertor impurity seeding based on real-time measurements of surface heat flux in the Alcator C-Mod tokamak

Mitigation of the intense heat flux to the divertor is one of the outstanding problems in fusion energy. One technique that has shown promise is impurity seeding, i.e., the injection of low-Z gaseous impurities (typically N2 or Ne) to radiate and dissipate the power before it arrives to the divertor target plate. To this end, the Alcator C-Mod team has created a first-of-its-kind feedback system to control the injection of seed gas based on real-time surface heat flux measurements. Surface thermocouples provide real-time measurements of the surface temperature response to the plasma heat flux. The surface temperature measurements are inputted into an analog computer that "solves" the 1-D heat transport equation to deliver accurate, real-time signals of the surface heat flux. The surface heat flux signals are sent to the C-Mod digital plasma control system, which uses a proportional-integral-derivative (PID) algorithm to control the duty cycle demand to a pulse width modulated piezo valve, which in turn controls the injection of gas into the private flux region of the C-Mod divertor. This paper presents the design and implementation of this new feedback system as well as initial results using it to control divertor heat flux

Characterizing the Hydrology of Shallow Floodplain Lakes in the Slave River Delta, NWT, Canada, Using Water Isotope Tracers

The relative importance of major hydrological processes on thaw season 2003 lakewater balances in the Slave River Delta, NWT, Canada, is characterized using water isotope tracers and total suspended sediment (TSS) analyses. A suite of 41 lakes from three previously recognized biogeographical zones—outer delta, mid-delta, and apex—were sampled immediately following the spring melt, during summer, and in the fall of 2003. Oxygen and hydrogen isotope compositions were evaluated in the context of an isotopic framework calculated from 2003 hydroclimatic data. Our analysis reveals that flooding from the Slave River and Great Slave Lake dominated early spring lakewater balances in outer and most mid-delta lakes, as also indicated by elevated TSS concentrations (\u3e0.01 g L-1). In contrast, the input of snowmelt was strongest on all apex and some mid-delta lakes. After the spring melt, all delta lakes underwent heavy-isotope enrichment due to evaporation, although lakes flooded by the Slave River and Great Slave Lake during the spring freshet continued to be more depleted isotopically than those dominated by snowmelt input. The isotopic signatures of lakes with direct connections to the Slave River or Great Slave Lake varied throughout the season in response to the nature of the connection. Our findings provide the basis for identifying three groups of lakes based on the major factors that control their water balances: (1) flood-dominated (n=10), (2) evaporation-dominated (n=25), and (3) exchange-dominated (n=6) lakes. Differentiation of the hydrological processes that influence Slave River Delta lakewater balances is essential for ongoing hydroecological and paleohydrological studies, and ultimately, for teasing apart the relative influences of variations in local climate and Slave River hydrology

Life below excellence: exploring the links between top-ranked universities and regional competitiveness

[EN] This paper examines interactions between the presence of top-ranked universities and other conditions that encourage regional competitiveness. Fuzzy-set qualitative comparative analysis (fsQCA) was conducted to assess the combined effect of the conditions. The analysis yields several noteworthy conclusions. First, no single condition is necessary for a region to be competitive. Second, R&D expenditure is important for regional competitiveness. Third, different configurations of conditions are sufficient for high competitiveness in different regional clusters. Furthermore, some of these configurations do not include the presence of top-ranked universities. A 'magic recipe' consists of the combination of a private research system, an inter-firm collaboration network and high levels of human capital. The analysis shows that university excellence is valuable. However, in terms of its contribution to regional development, it is not crucial and must always be contextualised. This conclusion is important for smart strategic planning of local knowledge systems.Jose-Maria Garcia-Alvarez-Coque and Francisco Mas-Verdu wish to thank Project RTI2018-093791-B-C22, funded by the Ministry of Science, Innovation and Universities (Spain), for supporting this research.García Alvarez-Coque, JM.; Mas Verdú, F.; Roig Tierno, H. (2021). Life below excellence: exploring the links between top-ranked universities and regional competitiveness. Studies in Higher Education. 46(2):369-384. https://doi.org/10.1080/03075079.2019.1637843S369384462Alamá-Sabater, L., Budí, V., García-Álvarez-Coque, J. M., & Roig-Tierno, N. (2019). Using mixed research approaches to understand rural depopulation. Economía Agraria y Recursos Naturales, 19(1), 99. doi:10.7201/earn.2019.01.06Baldacci, E., Clements, B., Gupta, S., & Cui, Q. (2008). Social Spending, Human Capital, and Growth in Developing Countries. World Development, 36(8), 1317-1341. doi:10.1016/j.worlddev.2007.08.003Bathelt, H., Malmberg, A., & Maskell, P. (2004). Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 28(1), 31-56. doi:10.1191/0309132504ph469oaBaumann, C., & Winzar, H. (2014). The role of secondary education in explaining competitiveness. Asia Pacific Journal of Education, 36(1), 13-30. doi:10.1080/02188791.2014.924387Berger, E. S. C. (2016). Is Qualitative Comparative Analysis an Emerging Method?—Structured Literature Review and Bibliometric Analysis of QCA Applications in Business and Management Research. FGF Studies in Small Business and Entrepreneurship, 287-308. doi:10.1007/978-3-319-27108-8_14Bjerke, L., & Johansson, S. (2015). Patterns of innovation and collaboration in small and large firms. The Annals of Regional Science, 55(1), 221-247. doi:10.1007/s00168-015-0712-yBoucher, G., Conway, C., & Van Der Meer, E. (2003). Tiers of Engagement by Universities in their Region’s Development. Regional Studies, 37(9), 887-897. doi:10.1080/0034340032000143896Bramwell, A., & Wolfe, D. A. (2008). Universities and regional economic development: The entrepreneurial University of Waterloo. Research Policy, 37(8), 1175-1187. doi:10.1016/j.respol.2008.04.016Breschi, S., & Lissoni, F. (2009). Mobility of skilled workers and co-invention networks: an anatomy of localized knowledge flows. Journal of Economic Geography, 9(4), 439-468. doi:10.1093/jeg/lbp008Camagni, R. (2017). Regional Competitiveness: Towards a Concept of Territorial Capital. Seminal Studies in Regional and Urban Economics, 115-131. doi:10.1007/978-3-319-57807-1_6Camagni, R., & Capello, R. (2013). Regional Competitiveness and Territorial Capital: A Conceptual Approach and Empirical Evidence from the European Union. Regional Studies, 47(9), 1383-1402. doi:10.1080/00343404.2012.681640Choi, J., & Lee, J. (2017). Repairing the R&D market failure: Public R&D subsidy and the composition of private R&D. Research Policy, 46(8), 1465-1478. doi:10.1016/j.respol.2017.06.009Cowan, R. (2000). The explicit economics of knowledge codification and tacitness. Industrial and Corporate Change, 9(2), 211-253. doi:10.1093/icc/9.2.211Cowan, R., & Zinovyeva, N. (2013). University effects on regional innovation. Research Policy, 42(3), 788-800. doi:10.1016/j.respol.2012.10.001Crilly, D. (2010). Predicting stakeholder orientation in the multinational enterprise: A mid-range theory. Journal of International Business Studies, 42(5), 694-717. doi:10.1057/jibs.2010.57Domenech, J., Escamilla, R., & Roig-Tierno, N. (2016). Explaining knowledge-intensive activities from a regional perspective. Journal of Business Research, 69(4), 1301-1306. doi:10.1016/j.jbusres.2015.10.096Duşa, A. (2008). A mathematical approach to the boolean minimization problem. Quality & Quantity, 44(1), 99-113. doi:10.1007/s11135-008-9183-xDuvivier, C., Polèse, M., & Apparicio, P. (2017). The location of information technology-led new economy jobs in cities: office parks or cool neighbourhoods? Regional Studies, 52(6), 756-767. doi:10.1080/00343404.2017.1322686European Commission. 2016a. European Regional Competitiveness Index. Brussels: Directorate-General for Regional and Urban Policy. Accessed June 2018. https://ec.europa.eu/regional_policy/en/information/maps/regional_competitiveness/.European Commission. 2016b. Regional Innovation Scoreboard (RIS). Brussels: Publications Office of the EU. Accessed June 2018. https://publications.europa.eu/en/publication-detail/-/publication/693eaaba-de16-11e6-ad7c-01aa75ed71a1/language-en/format-PDF/source-31233711.Fan, D., Li, Y., & Chen, L. (2017). Configuring innovative societies: The crossvergent role of cultural and institutional varieties. Technovation, 66-67, 43-56. doi:10.1016/j.technovation.2017.05.003Fiss, P. C. (2011). Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research. Academy of Management Journal, 54(2), 393-420. doi:10.5465/amj.2011.60263120Garcia-Alvarez-Coque, J.-M., Mas-Verdu, F., & Sanchez García, M. (2014). Determinants of Agri-food Firms’ Participation in Public Funded Research and Development. Agribusiness, 31(3), 314-329. doi:10.1002/agr.21407García Álvarez-Coque, J. M., Mas-Verdú, F., & Roig-Tierno, N. (2016). Technological innovation versus non-technological innovation: different conditions in different regional contexts? Quality & Quantity, 51(5), 1955-1967. doi:10.1007/s11135-016-0394-2Grossman, J. H., Reid, P. P., & Morgan, R. P. (2001). The Journal of Technology Transfer, 26(1/2), 143-152. doi:10.1023/a:1007848631448Harrison, R. T., & Leitch, C. M. (2005). Entrepreneurial Learning: Researching the Interface between Learning and the Entrepreneurial Context. Entrepreneurship Theory and Practice, 29(4), 351-371. doi:10.1111/j.1540-6520.2005.00089.xHarrison, J., & Turok, I. (2017). Universities, knowledge and regional development. Regional Studies, 51(7), 977-981. doi:10.1080/00343404.2017.1328189Hazelkorn, E. (2008). Learning to Live with League Tables and Ranking: The Experience of Institutional Leaders. Higher Education Policy, 21(2), 193-215. doi:10.1057/hep.2008.1Hewitt-Dundas, N., & Roper, S. (2011). Creating advantage in peripheral regions: The role of publicly funded R&D centres. Research Policy, 40(6), 832-841. doi:10.1016/j.respol.2011.03.005Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). Bibliometrics: The Leiden Manifesto for research metrics. Nature, 520(7548), 429-431. doi:10.1038/520429aJaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations. The Quarterly Journal of Economics, 108(3), 577-598. doi:10.2307/2118401Jaumotte, F., and N. Pain. 2005. “From Ideas to Development: The Determinants of R&D and Patenting.” OECD Economics Department Working Papers, No. 457, OECD Publishing (NJ1).Kitson, M., Martin, R., & Tyler, P. (2004). Regional Competitiveness: An Elusive yet Key Concept? Regional Studies, 38(9), 991-999. doi:10.1080/0034340042000320816Lasagni, A. (2012). How Can External Relationships Enhance Innovation in SMEs? New Evidence for Europe*. Journal of Small Business Management, 50(2), 310-339. doi:10.1111/j.1540-627x.2012.00355.xLee, S., Park, G., Yoon, B., & Park, J. (2010). Open innovation in SMEs—An intermediated network model. Research Policy, 39(2), 290-300. doi:10.1016/j.respol.2009.12.009Lilles, A., & Rõigas, K. (2015). How higher education institutions contribute to the growth in regions of Europe? Studies in Higher Education, 42(1), 65-78. doi:10.1080/03075079.2015.1034264Lim, M. A. (2017). The building of weak expertise: the work of global university rankers. Higher Education, 75(3), 415-430. doi:10.1007/s10734-017-0147-8Mairesse, J., & Mohnen, P. (2010). Using Innovation Surveys for Econometric Analysis. Handbook of the Economics of Innovation, 1129-1155. doi:10.1016/s0169-7218(10)02010-1Isabel Maria, B. F., Rossi, F., & Geuna, A. (2013). Collaboration objectives and the location of the university partner: Evidence from the Piedmont region in Italy. Papers in Regional Science, 93, S203-S226. doi:10.1111/pirs.12054Marino, M., Lhuillery, S., Parrotta, P., & Sala, D. (2016). Additionality or crowding-out? An overall evaluation of public R&D subsidy on private R&D expenditure. Research Policy, 45(9), 1715-1730. doi:10.1016/j.respol.2016.04.009Medzihorsky, J., I. Oana, M. Quaranta, and C. Schneider. 2016. “SetMethods: Functions for Set-theoretic Multi-method Research and Advanced QCA.” R package version 2.1.Miozzo, M., Desyllas, P., Lee, H., & Miles, I. (2016). Innovation collaboration and appropriability by knowledge-intensive business services firms. Research Policy, 45(7), 1337-1351. doi:10.1016/j.respol.2016.03.018Olcay, G. A., & Bulu, M. (2017). Is measuring the knowledge creation of universities possible?: A review of university rankings. Technological Forecasting and Social Change, 123, 153-160. doi:10.1016/j.techfore.2016.03.029Paruolo, P., Saisana, M., & Saltelli, A. (2012). Ratings and rankings: voodoo or science? Journal of the Royal Statistical Society: Series A (Statistics in Society), 176(3), 609-634. doi:10.1111/j.1467-985x.2012.01059.xPinch, S., Henry, N., Jenkins, M., & Tallman, S. (2003). From «industrial districts» to «knowledge clusters»: a model of knowledge dissemination and competitive advantage in industrial agglomerations. Journal of Economic Geography, 3(4), 373-388. doi:10.1093/jeg/lbg019Pinheiro, R., Benneworth, P., & Jones, G. A. (Eds.). (2012). Universities and Regional Development. doi:10.4324/9780203112298Ragin, C. C. (2008). Redesigning Social Inquiry. doi:10.7208/chicago/9780226702797.001.0001Ragin, C. C. (2014). The Comparative Method. doi:10.1525/9780520957350Roig-Tierno, N., Gonzalez-Cruz, T. F., & Llopis-Martinez, J. (2017). An overview of qualitative comparative analysis: A bibliometric analysis. Journal of Innovation & Knowledge, 2(1), 15-23. doi:10.1016/j.jik.2016.12.002Schneider, M. R., Schulze-Bentrop, C., & Paunescu, M. (2009). Mapping the institutional capital of high-tech firms: A fuzzy-set analysis of capitalist variety and export performance. Journal of International Business Studies, 41(2), 246-266. doi:10.1057/jibs.2009.36Schneider, C. Q., & Wagemann, C. (2012). Set-Theoretic Methods for the Social Sciences. doi:10.1017/cbo9781139004244SCImago. 2016. Scimago Institutions Ranking. Accessed June 2018. https://www.scimagoir.com.Shapira, P., & Youtie, J. (2008). Learning to Innovate: Building Regional Technology Development Learning Networks in Midsized Cities. European Planning Studies, 16(9), 1207-1228. doi:10.1080/09654310802401631Soete, L., B. Verspagen, and T. Ziesemer. 2017. “The Productivity Effect of Public R&D in the Netherlands (No. 021).” United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).Suri, T., Boozer, M. A., Ranis, G., & Stewart, F. (2011). Paths to Success: The Relationship Between Human Development and Economic Growth. World Development, 39(4), 506-522. doi:10.1016/j.worlddev.2010.08.020Thiem, A. (2014). Analyzing multilevel data with QCA: yet another straightforward procedure. Quality & Quantity, 50(1), 121-128. doi:10.1007/s11135-014-0140-6Tobiassen, A. E., & Pettersen, I. B. (2017). Exploring open innovation collaboration between SMEs and larger customers. Baltic Journal of Management, 13(1), 65-83. doi:10.1108/bjm-01-2017-0018Van Raan, A. F. J. (2005). Fatal attraction: Conceptual and methodological problems in the ranking of universities by bibliometric methods. Scientometrics, 62(1), 133-143. doi:10.1007/s11192-005-0008-6Vis, B. (2012). The Comparative Advantages of fsQCA and Regression Analysis for Moderately Large-N Analyses. Sociological Methods & Research, 41(1), 168-198. doi:10.1177/0049124112442142Wolfe, D. A. (2005). 10. The Role of Universities in Regional Development and Cluster Formation. Creating Knowledge, Strengthening Nations, 167-194. doi:10.3138/9781442673564-013World Bank. (2017). GDP Per Capita in US Dollars. World Bank National Accounts Data, and OECD National Accounts Data Files. https://data.worldbank.org/indicator/ny.gdp.pcap.cd.Youtie, J., & Shapira, P. (2008). Building an innovation hub: A case study of the transformation of university roles in regional technological and economic development. Research Policy, 37(8), 1188-1204. doi:10.1016/j.respol.2008.04.01

The Organic Research Centre; Elm Farm Bulletin 84 July 2006

Regular bulletin with technical updates of the Organic Advisory Service Issue contains: Battling on for Avian Flu preventive vaccination; Organic Colombian Blacktail eggs; UK Co-existence - GMOand non-GMO crops; Aspects of Poultry Behaviour; CAP in the service of biodiversity; Seeing the Wood, the Trees and the Catch 22; Beware of organic market "statistics"; A central role in energy review

The Deuterium Abundance at z=0.701 towards QSO 1718+4807

We present constraints on the deuterium to hydrogen ratio (D/H) in the metal-poor gas cloud at redshift $z=0.701$ towards QSO 1718+4807. We use new Keck spectra in addition to Hubble Space Telescope (HST) and International Ultraviolet Explorer (IUE) spectra. We use an improved redshift and a lower \HI column density to model the absorption. The HST spectrum shows an asymmetric Lyman-$\alpha$ (\lya) feature which is produced by either \HI at a second velocity, or a high abundance of D. Three models with a single simple H+D component give $8 \times 10^{-5} < D/H < 57 \times 10^{-5}$ (95%), a much larger range than reported by Webb et al (1997a,b). A more sophisticated velocity distribution, or a second component is necessary for lower D/H. With two components, which could be a part of one absorbing structure, or separate clouds in a galaxy halo, we find $D/H < 50 \times 10^{-5}$. We do not know if this second component is present, but it is reasonable because 40 -- 100% of absorption systems with similar redshifts and \HI column densities have more than one component.Comment: 13 pages, 4 figures, to appear in the Astronomical Journal (Jan 1999

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Appendix A: ROBSIM user's guide

The purpose of the Robotics Simulation Program is to provide a broad range of computer capabilities to assist in the design, verification, simulation, and study of robotics systems. ROBSIM is program in FORTRAN 77 for use on a VAX 11/750 computer under the VMS operating system. This user's guide describes the capabilities of the ROBSIM programs, including the system definition function, the analysis tools function and the postprocessor function. The options a user may encounter with each of these executables are explained in detail and the different program prompts appearing to the user are included. Some useful suggestions concerning the appropriate answers to be given by the user are provided. An example user interactive run in enclosed for each of the main program services, and some of the capabilities are illustrated