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The USA has a rapidly aging prison population that, combined with their poorer health and living conditions, is at extreme risk for COVID-19. The purpose of this paper is to compare COVID-19 mortality trends in the US prison population and the general population to see how mortality risk changed over the course of the pandemic. The authors first provide a national overview of trends in COVID-19 mortality; then, the authors assess COVID-19 deaths among older populations using more detailed data from one US state.

The authors used multiple publicly available data sets (e.g. Centers for Disease Control and prevention, COVID Prison Project) and indirect and direct standardization to estimate standardized mortality rates covering the period from April 2020 to June 2021 for the US and for the State of Texas.

While 921 COVID-19-related deaths among people in US prisons were expected as of June 5, 2021, 2,664 were observed, corresponding to a standardized mortality ratio of 2.89 (95%CI 2.78, 3.00). The observed number of COVID-19-related deaths exceeded the expected number of COVID-19-related deaths among people in prison for most of the pandemic, with a substantially widening gap leading to a plateau about four weeks after the COVID-19 vaccine was introduced in the USA. In the state population, the older population in prison is dying at younger ages compared with the general population, with the highest percentage of deaths among people aged 50–64 years.

People who are incarcerated are dying of COVID-19 at a rate that far outpaces the general population and are dying at younger ages.

This descriptive analysis serves as a first step in understanding the dynamic trends in COVID-19 mortality and the association between age and COVID-19 death in US prisons.

The purpose of this research is to compare two different sample populations (student and general) to determine the impact of brand community motives on brand community engagement.

Two samples were drawn for the purpose of the current research. The first sample was drawn among the members of various brand communities from a general North American population sample (N = 503). The second sample was drawn purely from students, belonging to a variety of brand communities, from a middle-sized Canadian university (N = 195). Partial least squares structural equation modelling was used to analyse the strength, significance and effect sizes of the relationships between brand community motive and engagement constructs.

The findings indicate that the impact of brand community motives varied by sample population. The information and entertainment motives were significantly related to brand community engagement in both sample populations with roughly equal effect sizes. The social integration motive was again significantly related to the brand community engagement construct in the student sample population – but not for the general North American general population sample. Further, the self-discovery motive and status enhancement motives were significantly related to brand community engagement in the North American sample, but not for the student sample. This indicates significant differences between the two sample populations.

The results of the current research demonstrate that student populations are significantly different from the general population regarding their motives towards brand communities. This indicates that brand community managers need to be aware of the motives of different brand community members and also that they need to exercise caution about utilizing purely student data to make decisions about brand community management.

This chapter presents a brief description of the development of capitalism in Argentina, focusing on the situation of the working class and its practices. It analyzes the relationship between the main directions of capitalist development and the means of struggle used by the working class for more than a hundred years. It describes the predominant tendencies (in breadth and depth) of the development of capitalism in Argentina and the consequent main direction of the movement of the population (attraction or repulsion) in relation to capitalist relations. From the nineteenth century to the mid-seventies of the twentieth century, capitalism developed mainly in breadth, incorporating population, general strikes became a frequent practice and workers achieved a place in the institutional system. In the last quarter of the twentieth century, capitalist developed mainly in depth and, consequently, repulsion of population became dominant, increasing unemployment and poverty. Workers’ organizations lost some of their strength, but new organizations of the unemployed and the poor emerged, and roadblocks extended as an instrument of struggle.

The purpose of this paper is to provide a comprehensive review of the respondents’ fraud phenomenon in online panel surveys, delineate data quality issues from surveys of broad and narrow populations, alert fellow researchers about higher incidence of respondents’ fraud in online panel surveys of narrow populations, such as logistics professionals and recommend ways to protect the quality of data received from such surveys.

This general review paper has two parts, namely, descriptive and instructional. The current state of online survey and panel data use in supply chain research is examined first through a survey method literature review. Then, a more focused understanding of the phenomenon of fraud in surveys is provided through an analysis of online panel industry literature and psychological academic literature. Common survey design and data cleaning recommendations are critically assessed for their applicability to narrow populations. A survey of warehouse professionals is used to illustrate fraud detection techniques and glean additional, supply chain specific data protection recommendations.

Surveys of narrow populations, such as those typically targeted by supply chain researchers, are much more prone to respondents’ fraud. To protect and clean survey data, supply chain researchers need to use many measures that are different from those commonly recommended in methodological survey literature.

For the first time, the need to distinguish between narrow and broad population surveys has been stated when it comes to data quality issues. The confusion and previously reported “mixed results” from literature reviews on the subject have been explained and a clear direction for future research is suggested: the two categories should be considered separately.

Specific fraud protection advice is provided to supply chain researchers on the strategic choices and specific aspects for all phases of surveying narrow populations, namely, survey preparation, administration and data cleaning.

This paper can greatly benefit researchers in several ways. It provides a comprehensive review and analysis of respondents’ fraud in online surveys, an issue poorly understood and rarely addressed in academic research. Drawing from literature from several fields, this paper, for the first time in literature, offers a systematic set of recommendations for narrow population surveys by clearly contrasting them with general population surveys.

This chapter provides a historical overview of the data and methodologies used to measure worklife and the usefulness of such statistics for projecting future retirement behavior. Section 2 discusses the calculation of worklife expectancy (WLE), beginning with a review of the data and method of calculation using what has come to be known as the conventional model. Section 3 looks at the WLE results using the increment–decrement model and subsequent models. Sections 4 and 5 revisit the conventional model and compare the results of the conventional model to the increment-decrement model. Section 6 of the chapter discusses the data and methodologies used to calculate years to final separation (YFS), and Section 7 discusses the use of both WLE and YFS statistics in projecting future retirement behavior.

The labourforce status of members of American Mensa (a high IQ group) is examined. Compared with a general US sample, the Mensans′ labour‐force participation rate was found to be higher, while the percentage not in the labourforce was lower. Multinomial logit estimation indicates that demographic variables have greater influence on the odds of individuals being in the various labourforce categories for the general US sample than for Mensans. Differences in labourforce patterns for Mensans versus the US sample are due more to differences in characteristics than to underlying behavioural differences.

The purpose of the paper is to highlight the differences in literacy and schooling attainment among the scheduled tribe women in India.

The paper uses data from the Census of India, Department of Education in India, and National Human Development Report prepared by the Government of India.

The high status of women among the tribal groups in the northeastern states has important effects on the literacy rates, enrollment ratios and dropout rates of girls in that region. High‐poverty rates pose to be significant obstacles in attaining literacy and education among tribal women in India. However, large differences in literacy rates in the various states in India show that social and cultural norms, proximity to the mainstream Hindu culture, and the role of women are also important determinants in achieving literacy among tribal women.

Literacy is considered to be an important tool for improving the status of women among the scheduled tribes. Aggregate statistics often paint a dismal picture of the low‐literacy rates and schooling among the scheduled tribe women. This paper shows that such statistics fail to capture the different trends in literacy rates and value placed in schooling among the various tribal groups in India. Differences in economic, social, and cultural backgrounds among the various tribes need to be emphasized in order to understand the differential nature of investments in literacy rates and schooling among tribal women in India.

The purpose of this paper is to report on a research designed to find out how people in Scotland access and use online health information.

It is based on a survey of two sets of population in Glasgow – a group of 64 users from the general public and a group of 24 post graduate students from a university in Glasgow.

Use of the Internet for health information was found to be much lower in Scotland than in the previous UK studies particularly those using online surveys. It was noted that people searched online health information for themselves, family and friends. Healthy eating, exercise and alternative medicine were the most commonly sought topics. Approximately half the survey participants felt online health information influenced their treatment.

The study incorporates both Internet users and non‐users, as well as proficient internet users, and therefore provides a more balanced view.

Prisons can be epicentres of infectious diseases. However, empirical evidence on the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in prison is still scarce. This study aims to estimate the seroprevalence rates of anti-SARS-CoV-2 in the largest and most crowded Swiss prison and compare them with the seroprevalence rate in the general population.

A cross-sectional study was conducted in June 2020, one month after the first wave of SARS-CoV-2 in Switzerland. Groups included: people living in detention (PLDs) detained before the beginning of the pandemic (n = 116), PLDs incarcerated after the beginning of the pandemic (n = 61), prison staff and prison healthcare workers (n = 227) and a sample from the general population in the same time period (n = 3,404). The authors assessed anti-SARS-CoV-2 IgG antibodies.

PLDs who were incarcerated before the beginning of the pandemic had a significantly lower seroprevalence rate [0.9%, confidence interval (CI)95%: 0.1%–5.9%] compared to the general population (6.3%, CI 95%: 5.6–7.3%) (p = 0.041). The differences between PLDs who were incarcerated before and other groups were marginally significant (PLDs incarcerated after the beginning of the pandemic: 6.6%, CI 95%: 2.5%–16.6%, p = 0.063; prison staff CI 95%: 4.8%, 2.7%–8.6%, p = 0.093). The seroprevalence of prison staff was only slightly and non-significantly lower than that of the general population.

During the first wave, despite overcrowding and interaction with the community, the prison was not a hotspot of SARS-CoV-2 infection. Preventive measures probably helped avoiding clusters of infection. The authors suggest that preventive measures that impact social welfare could be relaxed when overall circulation in the community is low to prevent the negative impact of isolation.