Browsing by Subject "Stratification"

Subjective cultural meanings were once central to occupational stratification research. However, attempts to operationalize cultural meanings associated with occupations have been widely criticized, leading contemporary stratification scholars to largely abandon subjective measures in favor of objective characteristics. This leaves a gap in our understanding of how inequality is generated and maintained because Weber ([1958]) theorized that status, a form of social symbolic power based on cultural beliefs, represents one of the fundamental bases of inequality. Without an adequate method of operationalizing occupational symbolic meanings, the extent to which cultural beliefs influence stratified life outcomes remains largely unknown.

To address this, I used affect control theory, a quantitative general theory of

social action, and its measurement model, the semantic differential scale, to examine three issues regarding the relationship between cultural beliefs and stratified outcomes. Symbolic meaning was quantified into EPA ratings that measure three universal, affective dimensions: evaluation (good versus bad), potency (powerful versus weak), and activity (lively versus quiescent). Despite extensive support within structural social psychology, this approach has not been widely used in the field of stratification. In addition to providing a quantitative framework, because symbolic meanings are comprised of multiple dimensions, affect control theory's multidimensional construction allows for novel approaches not possible using unidimensional measures. The three chapters that follow use affect control theory and ratings of occupational meanings from a newly collected dictionary of affective meaning to address the occupational gender wage gap, the effect of occupational status on life chance outcomes, and the development and testing of a new measure of occupational status.

In this thesis, we explore techniques in statistics and persistent homology, which detect features among data sets such as graphs, triangulations and point cloud. We accompany our theorems with algorithms and experiments, to demonstrate their effectiveness in practice.

We start with the derivation of graph scan statistics, a measure useful to assess the statistical significance of a subgraph in terms of edge density. We cluster graphs into densely-connected subgraphs based on this measure. We give algorithms for finding such clusterings and experiment on real-world data.

We next study statistics on persistence, for piecewise-linear functions defined on the triangulations of topological spaces. We derive persistence pairing probabilities among vertices in the triangulation. We also provide upper bounds for total persistence in expectation.

We continue by examining the elevation function defined on the triangulation of a surface. Its local maxima obtained by persistence pairing are useful in describing features of the triangulations of protein surfaces. We describe an algorithm to compute these local maxima, with a run-time ten-thousand times faster in practice than previous method. We connect such improvement with the total Gaussian curvature of the surfaces.

Finally, we study a stratification learning problem: given a point cloud sampled from a stratified space, which points belong to the same strata, at a given scale level? We assess the local structure of a point in relation to its neighbors using kernel and cokernel persistent homology. We prove the effectiveness of such assessment through several inference theorems, under the assumption of dense sample. The topological inference theorem relates the sample density with the homological feature size. The probabilistic inference theorem provides sample estimates to assess the local structure with confidence. We describe an algorithm that computes the kernel and cokernel persistence diagrams and prove its correctness. We further experiment on simple synthetic data.

The goal of this dissertation is to articulate specific modes and mechanisms by which the process of an individual choosing an organization is shaped by (1) the status of the organization, and (2) the attributes of the chooser. I do this with three types of chooser attributes: individual demographics, neighborhood context, and cultural values; and in two settings: choosing a hospital for cancer treatment, and choosing a church to attend and contribute to financially. Chapters 1 and 2 use data from the SEER-Medicare linked database to demonstrate the relationship between chooser (patient) demographics, at both the individual and neighborhood levels, on the likelihood of choosing a "high-status" cancer hospital in California. Chapter 1 does this in multiple ways. First, it shows that a patient's propensity to seek treatment for their cancer is a function of the patient's race, sex, and age, and by the racial makeup of a patient's neighborhood. Second, it shows that a patient's propensity to leave California for treatment is a function of both patient attributes and attributes of the hospitals they choose. Finally, it shows that patient choice of high-status cancer hospitals is moderated by the educational level of the patient's neighborhood. Chapter 2 shows that patient choice of high-status cancer hospitals is moderated by both individual-level race and the racial composition of the patient's neighborhood. Chapter 3 uses data from multiple sources to describe the ways that congregants' cultural values interact with organizational status (denomination) in the church choice process. Specifically, I use the National Congregations study to demonstrate the organization-level returns to nondenominational status on both legitimacy (attendees) and performance (tithes). Nondenominational churches are uniquely successful, even when compared only to conservative churches. I then use over 45,000 individual-level responses from the nationally-representative Religious Landscape/Faith in Flux Survey and Congregational Life Studies to demonstrate the individual-level valuative mechanisms behind organizational returns to categorical ambiguity. Though the settings and attributes differ across the three chapters, they all point to a similar conclusion: candidate choice processes are shaped by attributes of both candidates and choosers, and a neglect of chooser attributes misses important stratification in the choice process.

Older women in the U.S. face greater risks of economic insecurity in comparison with other age groups and with men their own age. Although these risks have been documented in prior research, few studies investigate the life course mechanisms underlying women's retirement insecurity. This dissertation seeks to fill this gap by using a life course perspective and the theory of cumulative disadvantage to examine how women's earlier work and family experiences shape subsequent economic resources in retirement. The three major types of retirement resources in the U.S. - Social Security benefits, occupational pensions, and private retirement wealth - are considered. Analyses use a variety of modeling techniques and panel data from the Health and Retirement Study linked to restricted access Social Security Administration files. In addition, this dissertation specifically investigates retirement insecurity across birth cohorts of older women.

The first substantive chapter examines how Social Security benefit eligibility type is influenced by four major life course predictors: marital continuity, family timing, employment commitment, and cohort change. Social Security benefit type is an important indicator of retirement security for women because, despite nearly universal program coverage, benefit type is associated with differential economic security in retirement for women. Multinomial logit models demonstrate the importance of women's own paid employment histories for later benefit type. Receiving own worker Social Security benefits or being dually eligible for Social Security are more likely outcomes with increased employment experience. The second empirical chapter uses discrete-time even history models to examine the timing of women's access to occupation pension income. The timing of pension income receipt is relevant for women's retirement security because delayed access indicates a missing source of economic resources. Results reveal significant cohort differences in the timing of first pension receipt as well as the important roles of marital continuity and family timing for older women's access to occupational pension income. The final empirical chapter employs age-based growth models to examine differential trajectories of private retirement savings in early retirement (ages 51-65) across U.S. birth cohorts of women. This analysis examines both initial retirement wealth and wealth accumulation over time to understand how life course processes advantage some older women, but contribute to ongoing disadvantage for others as part of this third, major source of retirement security. Results from growth models reveal variation across birth cohorts as well as the negative effects of divorce for initial wealth holdings and growth in retirement wealth. Overall, this dissertation illustrates the importance of women's work and family experiences across the life course for the cumulative disadvantages they face in retirement. Moreover, each type of major retirement resource interacts with different aspects of women's prior work and family roles to produce economic outcomes in retirement.