A statistical approach for analyzing residential isolation and its determinants for immigrant communities: an application to the Montreal metropolitan region

The aim of this paper is to measure the net propensity to live in isolation for Montréal’s main immigrant communities and to identify specific profiles that are particularly isolated. For that purpose, a statistical approach is used based on individual determinants to compute standardized isolation indexes that take into account the socioeconomic composition of the different groups. The models we developed also reveal how individuals’ characteristics, such as generational status, date of migration, education, language abilities or income, affect their residential isolation. Results reveal that many individual characteristics have strong impacts on residential isolation, and that those impacts are not always the same among immigrant communities. Also, the low propensity to live in isolation observed for all immigrant communities suggests that the place stratification model is probably not relevant to explain the residential dynamics of immigrant communities in Montréal. However, some vulnerable groups are much more likely to live in isolation: Haitian and South Asian with low education, low-income Maghrebis, and Filipinos who arrived via the Live-in Caregivers program. Some wealthy groups are also more isolated, such as Italians arrived before 1981. Therefore, considering this wide heterogeneity among immigrant communities, studies on their residential dynamic should not consider them as a whole

Does size really matter?

review of Maximum Canada: Why 35 Million Canadians are Not Enough</jats:p

Projecting health trajectories in Europe using microsimulation

This working paper presents an innovative methodological framework for projecting the health of individuals with a set of risk factors using a microsimulation model. The model developed, called ATHLOS-Mic, projects the health of cohorts born before 1960 and a set of risk factors for the horizon 2060 for some European countries. It simulates the lives of individuals using statistical models that explicitly take into account interactions between the different dimensions, either biological and behavioral risk factors (smoking, obesity, depression, arterial hypertension and physical activity), socioeconomic characteristics (education), a health metric, and mortality. Using data from SHARE-HD, we used parameters from statistical models to project dynamically changes in risk factors with a set of covariates and their impact on a health metric. The health metric is then used to modulate the probability of survival. A set of analytical scenarios are built showing the effect of each risk factors on future health trajectories. Results show that driven by a better educational attainment, each generation will be healthier than the previous one at same age. In average, an individual of our base population will live about 18 more years, but only 5 in good health. The scenario removing the effect of having a low level of education on the health metric is the one having the largest effect on both the projected average health metric, the average number of years lived per person, and the average number of years lived in good health. Summing up, removing all risk factors would add 2 years of life, but 6 years in good health

Effects of Quasi-Static Aberrations in Faint Companion Searches

We present the first results obtained at CFHT with the TRIDENT infrared camera, dedicated to the detection of faint companions close to bright nearby stars. The camera's main feature is the acquisition of three simultaneous images in three wavelengths (simultaneous differential imaging) across the methane absorption bandhead at 1.6 micron, that enables a precise subtraction of the primary star PSF while keeping the companion signal. The main limitation is non-common path aberrations between the three optical paths that slightly decorrelate the PSFs. Two types of PSF calibrations are combined with the differential simultaneous imaging technique to further attenuate the PSF: reference star subtraction and instrument rotation to smooth aberrations. It is shown that a faint companion with a DeltaH of 10 magnitudes would be detected at 0.5 arcsec from the primary.Comment: 12 pages, 10 figures, to appear in Astronomy with High Contrast Imaging, EAS Publications Serie

Benefit from high intrarenal levels of gentamicin in the treatment of E. coli pyelonephritis

Benefit from high intrarenal levels of gentamicin in the treatment of E. coli pyelonephritis. The importance of high intrarenal levels of gentamicin on the outcome of experimental pyelonephritis was studied in rats receiving either a short course (three days) of gentamicin (G) alone or combined with a longer course (14 days) of ampicillin (A), cephalothin (C), or trimethoprim (T), or two weeks of therapy with ampicillin, cephalothin, trimethoprim and gentamicin given alone. While ampicillin, cephalothin and trimethoprim were undetectable in the medulla within six hours of cessation of therapy, gentamicin was still detectable in levels six folds above the MIC up to six months after treatment had ceased. Six months after the end of treatment, the percentage of sterile left kidneys in animals treated with ampicillin (50%), cephalothin (15%), trimethoprim (20%) was lower than the percentage of animals receiving 14 days of gentamicin (100%), or the combinations AG:89%, CG:67% and TG:60%, P < 0.01. Following three days of gentamicin, 50% of the left kidneys were sterilized. When compared to ampicillin, cephalothin or trimethoprim alone, combined therapies significantly reduced the number of CFU in the kidneys P < 0.01. These combinations were almost as effective as two weeks of therapy with gentamicin. Short–term therapy (three days) with an aminoglycoside which concentrates in the renal parenchyma, combined with an antibiotic which will accumulate in other parts of the nephron, may result in “pharmacological synergy”. This new approach to therapy of pyelonephritis may be promising

A Microsimulation Approach for Modelling the Future Human Capital of EU28 Member Countries

In knowledge-based economies, human capital is a major determinant of labor force participation and productivity and has received growing interest from researchers and policy makers alike. Recently, the Wittgenstein Centre for Demography and Global Human Capital (WiC) performed macro-level projections by age, sex and education for all countries in the world. Projections of education in this model are computed based on past trends at the macro level by cohort and sex. This working paper uses data from five waves of the European Social Survey and ordered logistic regressions to estimate the impact of additional dimensions on educational attainment in EU28 countries. Variables included in the model are cohort year, sex, religion, language, immigration status and education of the mother. Cohort analysis allowed us to estimate educational trends net of individual characteristics. Analysis showed that the most important determinant of educational attainment was the education of the mother, but that other ethno-cultural factors such as religion and language spoken at home also played a role. Cohort trends net of individual characteristics varied significantly from country to country, with many countries having low or even null improvement in educational attainment for recent cohorts, most notably in Eastern Europe. The parameters derived from this analysis are used as inputs to a European microsimulation model including several dimensions beyond age, sex and education, many of which will be used to assess future immigrant integration in Europe. Preliminary results from the projections show that net and gross trends yield similar results in many countries where net trends are still dominant, but significant differences emerge in other countries in which net trends are low or null. The microsimulation model also allows for a better appreciation of dynamics in population sub-groups, for instance in rising concerns about potentially growing inequalities, notably for Muslims

Implementing dynamics of immigration integration in labor force participation projection in EU28

Many developed countries have turned to immigration in order to mitigate the consequences of population aging, particularly the expected decline in the labor force population. Yet, few projection models take in consideration explicitly the differentials in labor force participation of population sub-groups. This paper describes the labor force participation module of CEPAM-Mic, which is a microsimulation model that projects several demographic, ethnocultural and socioeconomic dimensions of the EU28 member countries population. Then, the microsimulation model is used to project EU labor force population for the period 2015-2060 under different scenarios illustrating how implementing sex- and country-specific dynamics of immigrants’ integration may affect the future labor force in terms of size, rates and gender composition. We estimated the parameters of the labor force module using logistic regressions based on the EU-Labour Force Survey (EU-LFS). In addition to age, sex and education, immigrant-related variables are also included, such as immigrant status, place of birth, age at immigration and duration of residence in the estimation of the probability of being active. Our results demonstrate the importance of taking into account differentials in labor force participation of population sub-groups when asserting the potential of immigration as a tool for managing population aging. In the European context, adding immigration differentials in labor force participation affects mainly downward the number of female immigrants in the labor force, while smaller differences are observed for male immigrants. An increase in immigration levels leads obviously to an increase in the total labor force size, but may also widen gender inequalities in labor force participation and has limited impact on the total labor force participation rate. Our findings suggest that relying on immigration as a tool to alleviate economic issues arising from population aging must imperatively be accompanied by strong and efficient measures to promote a full economic integration of immigrants

Education Policies and Intergenerational Educational Mobility in China: New Evidence for the 1986–95 Birth Cohort

Research on educational mobility for Chinese born in or before 1976–85 abounds. Although the Compulsory Education Law implemented in 1986 and the expansion of higher education introduced in 1999 changed Chinese millennials’ educational achievements, little is known about the educational mobility for the 1986–95 birth cohort and where it stands in the long-term trends. In this study, we calculated population-level educational percentile ranks by birth cohort and gender using data from the 1982 to 2020 China Censuses before linking these ranks to respondents in Chinese General Social Survey (CGSS) or China Family Panel Studies (CFPS) to document 1986–95 birth cohort's educational mobility and its historical position. We also explored the role played by offspring's hukou origin (urban or rural) and ethnicity (Han or ethnic minorities). In the 1986–95 birth cohort, women's educational percentile ranks for secondary and tertiary levels fell below men's for the first time in China, suggesting that the proportion of women in higher education overtook men's. From 1976–85 to 1986–95 birth cohorts, while educational rank-rank correlations remained stable in all parent–child dyads and were constantly higher for offspring with urban hukou origin, there is suggestive evidence on increased educational mobility for women with rural hukou origin. Ethnicity differences were not found. Our findings imply that China's Compulsory Education Law and higher education expansion may have contributed to greater educational mobility for women with rural hukou origin in the 1986–95 birth cohort and their diminished disadvantage in education