Education and Skills: An Assessment of Recent Canadian Experience

The skills issue is currently at or near the top of the federal government’s policy agenda, given its importance for harnessing the benefits of technological advances. Policy initiatives in the area should be premised on an accurate assessment of Canada’s recent experience in education and skill formation. In his paper, W. Craig Riddell attempts such an assessment. He provides a careful examination of trends in education expenditures and outcomes in Canada compared to other countries, looks at trends in the incidence of education, and analyzes the link between education and labour market success. Riddell’s overall assessment of Canada’s record in education and skills is quite positive. He finds that relative to other OECD countries, Canada ranks near the top in terms of expenditure per student and share of GDP devoted to elementary, secondary and post-secondary education; that Canada’s population is well educated by international standards, with the highest proportion of the population with non-university, post-secondary education in the OECD; and that the country’s literacy skills, particularly for the young and well educated, are above average among the G7 countries that participated in the International Adult Literacy Survey. One possible weakness he identifies is the relatively low student achievement in mathematics among the G7 countries that participated in the standardized tests. This suggests Canada may not be obtaining good “value for money” from its relatively high expenditure on education. Riddell notes that the conventional estimates of the return to education appear downward biased so that the causal effect of education on earnings may be higher than previously believed. Evidence suggests that the marginal return to incremental investment in education exceeds the average from previous investments and that there is no evidence that investments in schooling are running into diminishing returns. Riddell concludes that investments in human capital remain an important potential source of economic growth and equality of opportunity.Education, Human Capital, Skills, Literacy, Numeracy, Canada, Post-secondary, Postsecondary, Post Secondary, Earnings, Return To Education

Rmax: A systematic approach to evaluate instrument sort performance using center stream catch.

Sorting performance can be evaluated with regard to Purity, Yield and/or Recovery of the sorted fraction. Purity is a check on the quality of the sample and the sort decisions made by the instrument. Recovery and Yield definitions vary with some authors regarding both as how efficient the instrument is at sorting the target particles from the original sample, others distinguishing Recovery from Yield, where the former is used to describe the accuracy of the instrument's sort count. Yield and Recovery are often neglected, mostly due to difficulties in their measurement. Purity of the sort product is often cited alone but is not sufficient to evaluate sorting performance. All of these three performance metrics require re-sampling of the sorted fraction. But, unlike Purity, calculating Yield and/or Recovery calls for the absolute counting of particles in the sorted fraction, which may not be feasible, particularly when dealing with rare populations and precious samples. In addition, the counting process itself involves large errors. Here we describe a new metric for evaluating instrument sort Recovery, defined as the number of particles sorted relative to the number of original particles to be sorted. This calculation requires only measuring the ratios of target and non-target populations in the original pre-sort sample and in the waste stream or center stream catch (CSC), avoiding re-sampling the sorted fraction and absolute counting. We called this new metric Rmax, since it corresponds to the maximum expected Recovery for a particular set of instrument parameters. Rmax is ideal to evaluate and troubleshoot the optimum drop-charge delay of the sorter, or any instrument related failures that will affect sort performance. It can be used as a daily quality control check but can be particularly useful to assess instrument performance before single-cell sorting experiments. Because we do not perturb the sort fraction we can calculate Rmax during the sort process, being especially valuable to check instrument performance during rare population sorts.Andrew Riddell is based at the Wellcome Trust-MRC Stem Cell Institute, Centre for Stem Cell Research University of CambridgeThis is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S104620231500090

Urban air quality citizen science. Phase 1: review of methods and projects

This report will comprise suggestions of links with other work and possible approaches for taking the work forward, providing a map of current and recent air quality related Citizen Science activities in the UK, Europe and beyond. In this deliverable, we map out the technologies and approaches currently available for air quality monitoring and provide an overview on how they could be applied in a citizen science context. In addition, we provide an overview of existing citizen science activities with relevance to air pollution. The focus of this report will be on the specific aspects of air pollution monitoring in a citizen science context; we refer to Roy et al. (2012) for a more general discourse on citizen science projects. As far as possible, we will closely link to another SEPA funded project with a focus on citizen science for environmental monitoring (by direct personal contact with colleagues at CEH), as well as other ongoing and emerging projects (e.g. EU FP7 project CitiSense, Transport Scotland, etc.). The objective of this report is not to draw final conclusions, but to provide the material and information resources for the following phases 2 and 3 of the pilot project

Stan: A Probabilistic Programming Language

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting

Some remarks on the equation of state for hard repulsive potentials

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32291/1/0000358.pd

Contraceptive use and pregnancy planning in Britain during the first year of the COVID-19 pandemic: findings from a large, quasi-representative survey (Natsal-COVID)

BACKGROUND: Contraceptive services were significantly disrupted during the COVID-19 pandemic in Britain. We investigated contraception-related health inequalities in the first year of the pandemic. METHODS: Natsal-COVID Wave 2 surveyed 6658 adults aged 18-59 years between March and April 2021, using quotas and weighting to achieve quasi-representativeness. Our analysis included sexually active participants aged 18-44 years, described as female at birth. We analysed contraception use, contraceptive switching due to the pandemic, contraceptive service access, and pregnancy plannedness. RESULTS: Of 1488 participants, 1619 were at risk of unplanned pregnancy, of whom 54.1% (51.0%-57.1%) reported routinely using effective contraception in the past year. Among all participants, 14.3% (12.5%-16.3%) reported switching or stopping contraception due to the pandemic. 3.2% (2.0%-5.1%) of those using effective methods pre-pandemic switched to less effective methods, while 3.8% (2.5%-5.9%) stopped. 29.3% (26.9%-31.8%) of at-risk participants reported seeking contraceptive services, of whom 16.4% (13.0%-20.4%) reported difficulty accessing services. Clinic closures and cancelled appointments were commonly reported pandemic-related reasons for difficulty accessing services. This unmet need was associated with younger age, diverse sexual identities and anxiety symptoms. Of 199 pregnancies, 6.6% (3.9%-11.1%) scored as 'unplanned'; less planning was associated with younger age, lower social grade and unemployment. CONCLUSIONS: Just under a third of participants sought contraceptive services during the pandemic and most were successful, indicating resilience and adaptability of service delivery. However, one in six reported an unmet need due to the pandemic. COVID-induced inequalities in service access potentially exacerbated existing reproductive health inequalities. These should be addressed in the post-pandemic period and beyond

Initial Impacts of COVID-19 on Sex Life and Relationship Quality in Steady Relationships in Britain: Findings from a Large, Quasi-representative Survey (Natsal-COVID)

Intimate relationships are ubiquitous and exert a strong influence on health. Widespread disruption to them may impact wellbeing at a population level. We investigated the extent to which the first COVID-19 lockdown (March 2020) affected steady relationships in Britain. In total, 6,654 participants aged 18-59 years completed a web-panel survey (July-August 2020). Quasi-representativeness was achieved via quota sampling and weighting. We explored changes in sex life and relationship quality among participants in steady relationships (n = 4,271) by age, gender, and cohabitation status, and examined factors associated with deterioration to a lower-quality relationship. A total of 64.2% of participants were in a steady relationship (of whom 88.9% were cohabiting). A total of 22.1% perceived no change in their sex-life quality, and 59.5% no change in their relationship quality. Among those perceiving change, sex-life quality was more commonly reported to decrease and relationship quality to improve. There was significant variation by age; less often by gender or cohabitation. Overall, 10.6% reported sexual difficulties that started/worsened during lockdown. In total, 6.9% reported deterioration to a "lower quality" relationship, more commonly those: aged 18-24 and aged 35-44; not living with partner (women only); and reporting depression/anxiety and decrease in sex-life quality. In conclusion, intimate relationship quality is yet another way in which COVID-19 has led to divergence in experience