What’s in an Occupation? Investigating Within-Occupation Variation and Gender Segregation Using Job Titles and Task Descriptions

Occupations have long been central to the study of inequality and mobility. However, the occupational categories typical in most U.S. survey data conceal potentially important patterns within occupations. This project uses a novel data source that has not previously been released for analysis: the verbatim text responses provided by respondents to the General Social Survey from 1972 to 2018 when asked about their occupation. These text data allow for an investigation of variation within occupations, in terms of job titles and task descriptions, and the occupation-level factors associated with this variation. I construct an index of occupational similarity based on the average pairwise cosine similarity between job titles and between task descriptions within occupations. Findings indicate substantial variation in the level of similarity across occupations. Occupational prestige, education, and income are associated with less heterogeneity in terms of job titles but slightly more heterogeneity in terms of task descriptions. Gender diversity is associated with more internal heterogeneity in terms of both job titles and task descriptions. In addition, I use the case of gender segregation to demonstrate how occupational categories can conceal the depth and form of stratification.

Knowledge, attitude, and practice toward COVID-19 in Trinidad and Tobago

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) has affected over 250 million people globally and resulted in over 5 million deaths since it was first reported in November 2019. Methods: A cross-sectional study was conducted online from July to September 2020 among nationals and permanent residents of Trinidad and Tobago (N = 812). The related questionnaire consisted of demographic characteristics, 11 items on knowledge, 11 items on attitude and 7 items on practice and experience. Domain scores were derived for each component (K, A and P) and independent t-tests and one-way ANOVA were used to compare differences in scores within demographic categories. Results: The population possessed a high level of knowledge about COVID-19(0.85 ± 0.09). Attitude scores (0.54 ± 0.07) were influenced by factors such as sex, age, occupation, level of education and area of residence. Significant relationships (P<0.05) were found between demographic categories of sex, age, profession, education, geographical region and the mean domain scores. Conclusion: There was overall high level of knowledge and good practices in response to COVID-19 which suggests that the government's management approach was effective in providing information about COVID-19 and the safe practice needed to reduce spread of the virus.

The relative effect of student, family and school-related factors on math achievement by location of the school

This study aims to examine the relative effects of student, family and school-related characteristics on 4th grade students’ math achievement according to location of the school in Turkey. The data of 6435 students studying at 260 primary schools were analyzed using TIMSS-2015 database. The dependent variable of the study was students’ math scores and 19 factors constituting the student, family and school-related characteristics were the independent variables. The location of the school was classified as urban, suburban, medium-size city and village. The data was analyzed via single level multiple linear regression. The results revealed that the entire models explained the largest amount of variance (52%) in the schools located in the villages and the least amount of variance (44%) in those located in the urban area. Although all of the student, family and school-related characteristic sets were found to be significantly related with the achievement, the student-related characteristics explained the largest amount of variance in achievement. Students’ confidence in math contributed almost the highest amount of variance, and the early numeracy tasks, absenteeism in school, parents’ highest education level, parents’ highest occupation level, early numeric activities before school explained small amounts of variance in students’ math achievement in the schools of all locations.

Blue-collared Workers’ Travel Behavior Modeling using “exPlainable” Machine Learning Model: The Case of Qatar

This paper presents a novel study on the examination of explainable machine learning (ML) technique to predict the mode choice for communities with a majority of blue-collared workers. A total of 4875 trip records for 1050 blue-collared workers have been used to predict their travel mode choices based on 11 trips and socio-economic attributes. The data used in this paper are obtained from the Ministry of Transportation and Communication (MoTC), which targeted blue-collared workers as they represent 89% of the total population in the State of Qatar. A total of four ML models are evaluated to propose the best predictive model. The four models were examined using different performance metrics. The models’ prediction results showed that the random forest (RF) model had the highest accuracy with a predictive accuracy of 0.97. Moreover, SHapley Additive exPlanation (SHAP) approach is used to investigate the significance of the input features and explain the output of the RF model. The results of SHAP analysis revealed that occupation level is the most significant feature that influences the mode choice followed by occupation section, arrival time, and arrival municipality.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study

Aims: To assess SARS-CoV-2 seroprevalence over the first epidemic wave in the canton of Geneva, Switzerland, as well as risk factors for infection and symptoms associated with IgG seropositivity. Methods: Between April and June 2020, former participants of a representative survey of the 20–74-year-old population of canton Geneva were invited to participate in the study, along with household members aged over 5 years. Blood samples were tested for anti-SARS-CoV-2 immunoglobulin G. Questionnaires were self-administered. We estimated seroprevalence with a Bayesian model accounting for test performance and sampling design. Results: We included 8344 participants, with an overall adjusted seroprevalence of 7.8% (95% credible interval 6.8–8.9). Seroprevalence was highest among 18–49 year-olds (9.5%), and lowest in 5–9-year-old children (4.3%) and individuals >65 years (4.7-5.4%). Odds of seropositivity were significantly reduced for female retirees and unemployed men compared to employed individuals, and smokers compared to non-smokers. We found no significant association between occupation, level of education, neighborhood income and the risk of being seropositive. The symptom most strongly associated with seropositivity was anosmia/dysgeusia. Conclusions: Anti-SARS-CoV-2 population seroprevalence remained low after the first wave in Geneva. Socioeconomic factors were not associated with seropositivity in this sample. The elderly, young children and smokers were less frequently seropositive, although it is not clear how biology and behaviours shape these differences.

What’s in an Occupation? Investigating Within-Occupation Variation and Gender Segregation Using Job Titles and Task Descriptions

Occupations have long been central to the study of inequality and mobility. However, the occupational categories typical in most U.S. survey data conceal potentially important patterns within occupations. This project uses a novel data source that has not previously been released for analysis: the verbatim text responses provided by respondents to the General Social Survey from 1972 to 2018 when asked about their occupation. These text data allow for an investigation of variation within occupations, in terms of job titles and task descriptions, and the occupation-level factors associated with this variation. I construct an index of occupational similarity based on the average pairwise cosine similarity between job titles and between task descriptions within occupations. Findings indicate substantial variation in the level of similarity across occupations. Occupational prestige, education, and income are associated with less heterogeneity in terms of job titles but slightly more heterogeneity in terms of task descriptions. Gender diversity is associated with more internal heterogeneity in terms of both job titles and task descriptions. In addition, I use the case of gender segregation to demonstrate how occupational categories can conceal the depth and form of stratification.

The effect of lack of citizenship on the wages of low-skilled non-permanent resident workers in Canada

This dissertation explores the effects of lack of citizenship on the wages of low-skilled Non-Permanent Residents (NPRs) in Canada—a category that includes temporary foreign workers, refugee claimants, and people with temporary resident visas on humanitarian grounds. The dissertation uses the 2006 census and quantitative methods (cross-tabulation and regression analysis) to evaluate wage differences between low-skilled workers without citizenship and low-skilled workers with citizenship or permanent resident status. Differences are calculated at the industry sector level and occupation level. The analysis further considers a set of intrinsic characteristics of low-skilled workers (including sex, level of education, official language ability and country of birth) and their occupations (provincial location, rural/urban setting). Empirically, this dissertation confirms that there is a penalty attached to lack of citizenship for low-skilled workers. In absolute terms, low-skilled NPRs earn low wages. In relative terms, these NPRs earn less than both the Canadian-born and immigrants low-skilled workers employed in the same occupations. Among low-skilled NPRs themselves, the Canadian labour market exhibits a hierarchy of wages and labour experiences on the lines of workers' country of birth, province of residence, and rural/urban place of work. Among low–skilled workers born in the same country, wages improve when either citizenship or the rights attached to permanent residence are acquired. From a policy perspective, the dissertation identifies the policy origins and drivers of low wages among low-skilled non-citizens. The thesis makes the case for the relevance of quantitative outcomes analyzed through a critical social lens. From a theoretical perspective too, the dissertation also shows how the state as a biased broker (towards capital) facilitates the implementation of non-citizenship as a means to accessing cheap labour.

The effect of lack of citizenship on the wages of low-skilled non-permanent resident workers in Canada

This dissertation explores the effects of lack of citizenship on the wages of low-skilled Non-Permanent Residents (NPRs) in Canada—a category that includes temporary foreign workers, refugee claimants, and people with temporary resident visas on humanitarian grounds. The dissertation uses the 2006 census and quantitative methods (cross-tabulation and regression analysis) to evaluate wage differences between low-skilled workers without citizenship and low-skilled workers with citizenship or permanent resident status. Differences are calculated at the industry sector level and occupation level. The analysis further considers a set of intrinsic characteristics of low-skilled workers (including sex, level of education, official language ability and country of birth) and their occupations (provincial location, rural/urban setting). Empirically, this dissertation confirms that there is a penalty attached to lack of citizenship for low-skilled workers. In absolute terms, low-skilled NPRs earn low wages. In relative terms, these NPRs earn less than both the Canadian-born and immigrants low-skilled workers employed in the same occupations. Among low-skilled NPRs themselves, the Canadian labour market exhibits a hierarchy of wages and labour experiences on the lines of workers' country of birth, province of residence, and rural/urban place of work. Among low–skilled workers born in the same country, wages improve when either citizenship or the rights attached to permanent residence are acquired. From a policy perspective, the dissertation identifies the policy origins and drivers of low wages among low-skilled non-citizens. The thesis makes the case for the relevance of quantitative outcomes analyzed through a critical social lens. From a theoretical perspective too, the dissertation also shows how the state as a biased broker (towards capital) facilitates the implementation of non-citizenship as a means to accessing cheap labour.

KNOWLEDGE AND PREVENTION PRACTICES OF HAND, FOOT AND MOUTH DISEASE AMONG PARENTS AND CAREGIVERS IN BANDAR PUNCAK ALAM, SELANGOR, MALAYSIA

Hand, Foot, and Mouth Disease (HFMD) is mainly caused by Coxsackievirus A16 (CVA16) and human Enterovirus A71 (EV-A71). Severe cases of HFMD were reported in Malaysia in 2018, which led to a temporary closing of few nurseries and preschools. A good knowledge and prevention practices is one of the important factors that can effectively decelerate this rapid outbreak of HFMD. Therefore, we conducted a survey to assess current knowledge and prevention practices among parents and caregivers in Bandar Puncak Alam, Selangor. A cross-sectional, questionnaire-based study was conducted on 345 residences of Bandar Puncak Alam, Selangor. It comprised of 77.4% (n=267) parents and 22.6% (n=78) caregivers from different daycares, kindergartens and preschools. The study showed that the majority, 87.2% (n=301) of Bandar Puncak Alam residents, Selangor have a moderate level of knowledge on HFMD. No significant difference in knowledge was found between parents and caregivers (p = 0.553). Age, occupation, level of education, and income of respondents influenced the HFMD knowledge level (p<0.05). Most parents and caregivers know how to prevent HFMD by practising cleaning the children's toys using liquid disinfection, but they are still lacking knowledge on the role of handwashing in preventing HFMD. In conclusion, the lack of prevention practice among parents and caregivers would increase the cases of HFMD. Therefore, a proper education of HFMD should be done to increase the awareness towards the prevention practices to prevent HFMD from reoccurring.

The Contribution of Occupation-Specific Factors to the Deaths of Despair, Massachusetts, 2005–2015

Objectives In the USA, deaths from poisonings (especially opioids), suicides, and alcoholic liver disease, collectively referred to as ‘deaths of despair’, have been increasing rapidly over the past two decades. The risk of deaths from these causes is known to be higher among certain occupations. It may be that specific exposures and experiences of workers in these occupations explain these differences in risk. This study sought to determine whether differences in the risk of deaths of despair were associated with rate of occupational injuries and illnesses, job insecurity, and temporal changes in employment in non-standard work arrangements. Methods Usual occupation information was collected from death certificates of Massachusetts residents aged 16–64 with relevant causes of death between 2005 and 2015. These data were combined with occupation-level data about occupational injuries and illnesses, job insecurity, and non-standard work arrangements. We calculated occupation-specific mortality rates for deaths of despair, categorized by occupational injury and illnesses rates and job insecurity. We calculated trends in mortality according to changes in non-standard work arrangements. Results Workers in occupations with higher injury and illnesses rates and more job insecurity had higher rates of deaths of despair, especially opioid-related deaths. Rates of deaths of despair increased most rapidly for occupations with increasing prevalence of workers employed in non-standard work arrangements. Conclusions The findings suggest occupational factors that may contribute to the risk of deaths of despair. Future studies should examine these factors with individual-level data. In the meantime, efforts should be made to address these factors, which also represent known or suspected hazards for other adverse health outcomes.