York University (French: Université York), also known as YorkU or simply YU, is a public research university in Toronto, Ontario, Canada. It is Canada's fourth-largest university, and it has approximately 55,700 students, 7,000 faculty and staff, and over 325,000 alumni worldwide. It has 11 faculties, including the Faculty of Liberal Arts and Professional Studies, Faculty of Science, Lassonde School of Engineering, Schulich School of Business, Osgoode Hall Law School, Glendon College, Faculty of Education, Faculty of Health, Faculty of Environmental and Urban Change, Faculty of Graduate Studies, School of the Arts, Media, Performance and Design, and 28 research centres.York University was established in 1959 as a non-denominational institution by the York University Act, which received royal assent in the Legislative Assembly of Ontario on 26 March of that year. Its first class was held in September 1960 in Falconer Hall on the University of Toronto campus with a total of 76 students. In the fall of 1961, York moved to its first campus, Glendon College, which was leased from U of T, and began to emphasize liberal arts and part-time adult education. In 1965, the university opened a second campus, the Keele Campus, in North York, within the neighbourhood community now called York University Heights.Several of York's programs have gained notable recognition both nationally and internationally. York houses Canada's oldest film school, which has been ranked one of the best in Canada, with an acceptance rate comparable to that of USC School of Cinematic Arts and Tisch School of the Arts. York's Osgoode Hall Law School was ranked fourth best in Canada, behind U of T, McGill, and UBC. In The Economist's 2011 full-time MBA rankings, York's Schulich School of Business ranked ninth in the world, and first in Canada, and in CNN Expansion's ranking of MBA programs, Schulich ranked 18th in the world, placing first in Canada. York's School of Kinesiology and Health Science ranked fourth in Canada and 24th best in the world in 2018.Over the last twenty years, York has become a centre for labour strife with several faculty and other strikes occurring, including the longest university strike in Canadian history in 2018. Its first class was held in September 1960 in Falconer Hall on the University of Toronto campus with a total of 76 students..
Stablecoins are increasingly discussed as an emerging form of digital tourism payment infrastructure. This study examines whether instability in stablecoins creates vulnerabilities in emerging tourism payment ecosystems by analysing the UST and USDC depeg events. Drawing on tourism systems theory, tourism resilience theory, and financial economics, the analysis combines high-frequency market data, on-chain transaction activity, and tourism payment indicators. The results show that depeg events degrade market quality by widening bid–ask spreads, reducing market depth, and increasing transaction costs. Large market participants also reduce risk-bearing and withdraw liquidity during periods of stress. In addition, depeg events strengthen dynamic correlations among closely linked stablecoins. Evidence from tourism payment activity suggests that severe depeg events may reduce the use of stablecoin-based payments within crypto-native tourism ecosystems. The findings suggest that instability in stablecoins may introduce settlement uncertainty and payment frictions within tourism ecosystems experimenting with blockchain-based payment infrastructure.
This research note examines the potential role of stablecoins as payment instruments within hospitality operations. Drawing on Transaction Cost Economics, UTAUT2, and Information Asymmetry Theory, the paper develops four proposals suggesting that stablecoins may reduce transaction frictions, improve settlement transparency, enhance customer experience, and support operational efficiency in digitally mediated hospitality environments. While adoption remains constrained by regulatory and managerial challenges, stablecoins are positioned as a complementary payment infrastructure that can deliver incremental operational improvements within hospitality organisations.
Objectives This study aimed to evaluate the technical feasibility of routine distributional analyses of healthcare interventions in Australia, by adapting a Health Inequality Impact Calculator for Queensland. Building on methods established in a previous study in England, the calculator compares the magnitude of health inequality impact across interventions for different diseases. Methods The calculator was adapted for adults in Queensland using the Index of Relative Socio-economic Advantage and Disadvantage quintiles, Australian Bureau of Statistics population estimates, 2023 hospital admissions (International Classification of Diseases-10th edition 3-digit level) from Queensland Health, and published quality-adjusted life expectancy. It was used to conduct aggregate distributional cost-effectiveness analysis of 5 interventions for diseases with relatively high prevalence in disadvantaged groups, based on existing cost-effectiveness results identified by a targeted review. The health inequality impact was summarized using the slope index of inequality in quality-adjusted life-years (QALYs). Results The selected interventions were 2 screening interventions for diabetes and hypertension, and 3 treatment interventions for chronic kidney disease. The calculator demonstrated that all 5 interventions would reduce health inequality. Population screening for diabetes had the greatest impact on reducing health inequality of 8562 QALYs. Among the 3 treatment interventions, intensive blood pressure control had the greatest impact, with a health inequality benefit of 514 QALYs. Conclusions Routine aggregate distributional cost-effectiveness analysis of interventions in Queensland is feasible, once standard cost-effectiveness estimates are available. The calculator for Queensland enables fast, transparent, and replicable analysis of health inequality impacts using minimal data, with visual outputs to explore trade-offs between health outcomes, inequality, and cost-effectiveness.
A multivariate transformation of the unit cube with component transformations that are piecewise continuously differentiable and uniform distribution preserving (udp) is considered. A stochastic inverse transformation is defined using randomization to overcome the non-injective nature of the udp transformations. The inverse transformation preserves the uniform margins of a random vector distributed according to a copula and yields different copulas for different randomizations. A copula density transformation result for the multivariate stochastic inverse is proved and illustrated in the bivariate case.
