I examine the passage of alternative teacher certification policies in the states between 1975 and 2000 using event history analysis and supplementing the event history analysis with an ordinary least squares regression analysis of the strength of the alternative teacher certification policies. In order to test both teachers unions political strength external to state legislatures and teachers unions political strength internal to state legislatures, I use two variables to measure teachers union political strength. One variable measures the percentage of teachers in a state who work under union-negotiated contracts. The other variable measures the percentage of legislators in a state who list their non-legislative occupation as K-12 education. Control variables include teacher shortages, per pupil spending, legislative professionalism, divided government, democratic governor, percentage of minority students, change in percentage of minority students, an electoral threat index, and a time counter. Although the event history model results were inconclusive with respect to the teachers union political strength variables, the policy strength model results reveal that states with large percentages of teachers who work under union-negotiated contracts are more likely than other states to pass weak alternative teacher certification policies. This result supports the notion that teachers unions operate in the education policy-making arena.

Why do states express support for norms that go against their underlying beliefs? Scholars of policy diffusion have identified four social mechanisms -- coercion, competition, emulation, and learning -- that can lead to the spread of a common practice, a norm, in the international system. I build a formal model of the four mechanisms and apply them to actual cases of norm diffusion. The formal models are anchored by three variables that capture fundamental aspects of international society: hierarchy, neighborhood, and identity. The four different diffusion mechanisms operate on these variables, creating distinct over-time trajectories. Three important dynamic patterns are compared across different model specifications: the shape of the adoption S-curve, the power distribution among expressers and non-expressers, and the degree of regional clustering. I find that the four mechanisms produce unique signatures under many conditions, but that changes to some parameters such as initial number of expressers can obscure the identification of the diffusion mechanism. In the first empirical chapter, I apply the framework to the diffusion of quotas for women's representation. I find that quotas are adopted by weak states, and that the likely source of inspiration for quota adoption are other weak states in the same neighborhood. The empirical pattern in terms of hierarchy, neighborhood, and identity point to competition as the mechanism that drove quota diffusion. Because competition is associated with norm internalization, this finding suggests that the world is really becoming more gender equal. In the second empirical chapter, I change substantive focus to the diffusion of human rights norms. Adoption of human rights treaties seems to be associated with worse human rights behavior, but why do states that ratify human rights treaties so often fail to uphold their obligations?. I find that the Convention Against Torture (CAT) treaty is adopted first by strong states in Europe, then to weaker states in a regionally-contingent pattern. This empirical pattern is most consistent with the emulation mechanism. This implies that the anti-torture norm is not associated with internalization, and solves the previously puzzling ratification-compliance paradox.

Using the multilevel framework, this multi-institutional study took different approaches to study undergraduate students’ retention in engineering programs. The study was conducted in two phases. In the first phase, using Multiple-Institution Database for Investigating Engineering Longitudinal Development, the aim was to control for macro-level factors which may create a selection bias in student admission into engineering programs. The outcome fed the second phase, which aimed to analyze student’s retention for different populations.

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Thesis advisor: Henry I. Braun / The City Connects intervention is motivated by the belief that out-of-school factors act as barriers to student thriving in cognitive and non-cognitive domains. It seeks to address these barriers first by identifying each student’s strengths and needs and then by providing a tailored set of prevention, intervention, and enrichment programs. Underlying the program is the assumption that provision of high-quality resources and individualized services will enable children to be cognitively, socio-emotionally, and physically prepared to thrive in school. This study’s purpose was to estimate the effects of the City Connects intervention on English learners’ (EL) likelihood of exiting Limited English Proficiency (LEP) status. ELs comprise a student subpopulation most at-risk to fail academically, and exposure to the program was hypothesized to improve their likelihood of exiting LEP status earlier than otherwise. A series of one- and two-level discrete-time event history analyses were conducted on the main analytic sample as well as two sub-samples. As participation in City Connects is at the school-level, school-level matching was used for sub-samples 1 and 2, and propensity score weights were applied at the student-level for all three samples. Additionally, hazard probabilities, survival probabilities, cumulative hazard rates, and median lifetimes were estimated. Lastly, a sensitivity analysis was conducted to examine whether effects were robust to unobserved selection bias. The results indicated that ELs participating in the City Connects intervention were significantly more likely to exit LEP status earlier than their peers in comparison schools. The median time in LEP status in City Connects schools was shorter and translated into a gain of at least one half of a year in grade in mainstream classes. Also, all the fitted models indicated that approximately 10 percent more City Connects students exited LEP status by the end of fifth grade than comparison students. Findings highlight the impact of the City Connects intervention, as ELs entering mainstream classes earlier could translate into important academic and non-academic gains, such as improved academic achievement and increased self-confidence. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

Sweden has seen a reversal in marriage trends, from mainly declining marriage rates since the 1960s to increasing rates from 1998 and onwards. By applying event-history techniques to Swedish register data, this study examines whether the trend reversal is related to compositional changes in various socio-economic and demographic characteristics of the population, with special focus on childbearing. Only first marriages of women are studied as these largely represent the general marriage trends. The results show that the trend reversal only partly can be ascribed to compositional changes, more specifically to changes in labor-market attachment and childbearing. Thus, there is evidence of a new marriage trend in Sweden that does not conform very well to that of generally declining marriage rates as is often depicted in demographic literature. Furthermore, there is evidence of pro-cyclical marriage and childbearing trends. These patterns are especially interesting because Sweden is a country that in many aspects has been a forerunner in the development of new trends in family-demographic behavior and a country where childbearing and marriage are not necessarily seen as very closely interrelated.

abstract: Time-to-event analysis or equivalently, survival analysis deals with two variables simultaneously: when (time information) an event occurs and whether an event occurrence is observed or not during the observation period (censoring information). In behavioral and social sciences, the event of interest usually does not lead to a terminal state such as death. Other outcomes after the event can be collected and thus, the survival variable can be considered as a predictor as well as an outcome in a study. One example of a case where the survival variable serves as a predictor as well as an outcome is a survival-mediator model. In a single survival-mediator model an independent variable, X predicts a survival variable, M which in turn, predicts a continuous outcome, Y. The survival-mediator model consists of two regression equations: X predicting M (M-regression), and M and X simultaneously predicting Y (Y-regression). To estimate the regression coefficients of the survival-mediator model, Cox regression is used for the M-regression. Ordinary least squares regression is used for the Y-regression using complete case analysis assuming censored data in M are missing completely at random so that the Y-regression is unbiased. In this dissertation research, different measures for the indirect effect were proposed and a simulation study was conducted to compare performance of different indirect effect test methods. Bias-corrected bootstrapping produced high Type I error rates as well as low parameter coverage rates in some conditions. In contrast, the Sobel test produced low Type I error rates as well as high parameter coverage rates in some conditions. The bootstrap of the natural indirect effect produced low Type I error and low statistical power when the censoring proportion was non-zero. Percentile bootstrapping, distribution of the product and the joint-significance test showed best performance. Statistical analysis of the survival-mediator model is discussed. Two indirect effect measures, the ab-product and the natural indirect effect are compared and discussed. Limitations and future directions of the simulation study are discussed. Last, interpretation of the survival-mediator model for a made-up empirical data set is provided to clarify the meaning of the quantities in the survival-mediator model. / Dissertation/Thesis / Doctoral Dissertation Psychology 2017

Financial aid contributes significantly to higher education participation in South Africa. However, while research focused on how financial aid improved access to University, little is known about its effect on ‘on-time' degree completion. Therefore, this research aimed to investigate to what extent financial aid affected the likelihood of on-time graduation as a function of selected student input and higher educational factors for students' success in studying towards a Bachelor of Commerce (BCom) at the University of Cape Town (UCT). To better understand the above factors, the researcher conducted a quantitative study applying Event History Analysis (EHA) and the Input-Environment-Output (I-E-O) model (Astin, 1993). A logistic regression within a discrete-time model with a personperiod dataset was performed. Data from the 2013 to 2018 UCT student records formed the basis of this research with a sample size of N=842. Based on the literature review, the input variables were gender, race, age, school type, final grade 12 marks and students' performance in the National Benchmark Tests (NBT). The environmental variables were enrollment in the academic development and support programme ‘Step-Up' and financial aid. Contrary to expectation, the results for the environmental variables surprisingly revealed that receiving financial aid decreased the likelihood of on-time graduation. Receiving GAP Aid indicated no statistically significant association with on-time graduation. Furthermore, enrolment in Step Up significantly increased the likelihood of on-time graduation, all else being equal. The findings for the input variables indicated that females and younger students were more likely to graduate on time than males and older students. White students were more likely to graduate on time than Black, Coloured and Indian/Asian students, which shows that this issue remains a transformation issue for Higher Education Institutions (HEIs). Another unexpected result was that the type of school attended and participation in NSC English indicated no association with on-time graduation. Most notably, students with NSC Accounting had a more significantly positive likelihood of on-time graduation than students with NSC Mathematics only. The research findings contribute value to the discussions on accounting education research and how to improve on-time degree completion. Secondly, the results could benefit policy decisions for student admission to the BCom programme. While the research results will reflect the nature of this specific university, the findings may also be valuable to other public HEIs with similar admission standards and student bodies.

This dissertation contributes to the disaster resilience policy literature by examining the diffusion of hazard mitigation policy in the U.S. Using the three-paper model, it investigates the adoption of local hazard mitigation plans (LHMPs) from an intergovernmental perspective. The first paper focuses on horizontal diffusion in hazard mitigation planning among local communities. Special attention is paid to the potential factors affecting the adoption of FEMA-approved LHMPs, Hazard Mitigation Grant Program (HMGP) projects and Pre-Disaster Program (PDM) projects at the county level. The Event History Analysis (EHA) Logit Model and Spatial Autocorrelation Models test the hypotheses corresponding to external factors such as the neighboring effects and internal factors, including disaster risks, neighborhood disadvantage and affluence, government capacity, local disaster resilience advocacy groups, and political support. The empirical results confirmed the significant influence of neighboring effects, indicating that counties are more likely to implement the same mitigation strategies if neighboring counties have done so. The results also revealed that disaster experience, government capacity, and strong democratic support significantly impact the likelihood of adopting LHMP and HMGP. Additionally, the results suggested that disadvantaged communities were more likely to adopt mitigation policies, while affluent communities were less likely to adopt such policies. The second paper evaluates the effectiveness of the FEMA's Program Administration by State Pilot (PAS). By integrating the Propensity Score Matching (PSM) technique with the Difference-in-Differences (DID) analysis, the empirical evidence demonstrated a significant reduction in the approval times for both LHMP and HMGP in pilot states compared to non-pilot states, with an average reduction nearing 30%. This suggests that the PAS program has effectively streamlined administrative processes, thereby enhancing efficiency in disaster management within pilot states. The analysis also indicated that the impact of PAS on the actual funding received through HMGP was insignificant, suggesting that while administrative processes were expedited, the allocation of financial resources remained unaffected. The third paper attempts to understand how local governments respond to top-down policy pressures in vertical diffusion by analyzing the text similarities of hazard mitigation strategies between state hazard mitigation plans and county LHMPs in Ohio using the word embedding technologies. The study employs the Word2Vec algorithm to assess the policy similarity between the hazard mitigation goals outlined in LHMPs and SHMPs. Building on this initial analysis, this research further uses the Beta Regression model to examine the textual similarities within LHMPs in Ohio, focusing on how the type of author - government versus private consultants, and the nature of the goals, whether action-based or hazard-based, affect these alignments. The regression analysis shows that LHMPs authored by government entities tend to exhibit higher textual similarity, reflecting the influence of standardized approaches driven by state and federal guidelines. This suggests a compliance-driven alignment in government-written plans. Conversely, LHMPs authored by private consultants display greater variability, suggesting that these plans are customized to the specific needs and risk assessments of local communities. Additionally, the regression results indicate that action-based and mixed-goal LHMPs are associated with higher textual similarity across counties. To carry out the empirical analysis mentioned above, this dissertation builds a panel dataset for all counties from 2000 to 2020, which contains data on LHMPs, HMA projects, disaster risks, socioeconomic characteristics, regional economic and political indicators, etc. / Doctor of Philosophy / Hazard mitigation in the United States is a critical issue, especially as the frequency and cost of disasters continue to rise. This dissertation investigates the dynamics of hazard mitigation planning within a multi-level governmental framework, focusing on the adoption of Federal Emergency Management Agency (FEMA) approved Local Hazard Mitigation Plans (LHMPs), Hazard Mitigation Grant Program (HMGP) projects, and Pre-Disaster Program (PDM) projects. across U.S. counties and the influence of federal and state policies on these local initiatives. The first paper examines the horizontal diffusion of LHMPs among local communities, revealing the significant influence of neighboring counties. This "neighboring effect" shows that counties are more likely to adopt similar mitigation strategies if their neighbors have done so, emphasizing the role of regional collaboration in spreading effective disaster resilience practices. Additionally, the study found that counties with more disaster experience and greater governmental capacity are more likely to implement LHMPs, highlighting the importance of preparedness and resources in driving policy adoption. Furthermore, this research finds counties with higher socioeconomic disadvantages are more proactive in adopting mitigation policies, which could be attributed to the higher perceived risks and available federal funding targeted at these communities. The second paper evaluates the impact of FEMA's Program Administration by State (PAS) pilot program on the administrative efficiency of LHMP and HMGP approvals. The findings indicate a significant reduction in approval times in pilot states, suggesting that the PAS program has successfully streamlined administrative processes. However, this expedited process did not lead to increased funding or broader adoption, pointing to the need for further policy enhancements to ensure that administrative improvements translate into real-world benefits for disaster preparedness. The third paper explores the vertical diffusion of policy from state to local governments, using Ohio as a case study. It employs advanced text analysis to measure the similarity between state and local hazard mitigation plans. The results show that government-authored LHMPs tend to closely follow state guidelines, indicating a top-down influence that ensures compliance with federal and state objectives. In contrast, LHMPs authored by private consultants were more varied and aligned to the specific needs and risks of local communities. This suggests that a balance is needed between standardized policies and local customization to effectively address the unique challenges of different regions. By integrating these findings, this dissertation provides a comprehensive overview of how hazard mitigation policies are adopted and implemented across various governmental levels. The research concludes with policy recommendations that advocate for sustained reforms in hazard mitigation funding, emphasizing the need for equitable resource distribution among disadvantaged communities. It also offers critical insights into improving intergovernmental cooperation and policy effectiveness, ensuring that all communities, regardless of their socio-economic status, can enhance their resilience and better prepare for future disasters. This research ultimately serves as a guide for policymakers to refine strategies that foster robust, community-centered resilience practices, enhancing the nation's overall disaster preparedness and response capabilities.

新竹科學園區對我國的社經發展有著卓越的貢獻，就2006年的統計數據來看，年營業額佔全國工業生產毛額的比率約35%，佔台灣GDP的比率則將近10%，佔全國出口貿易總值的8%，就業人數則約佔全國就業者的1.2%，其實質重要性可見一般，所以竹科廠商的存活是與全國、地方的社經發展緊密交織無可劃分，竹科廠商的退出可能會造成經濟成長停滯、工作機會短少、政策資源錯置等問題。 既有研究多半強調竹科成功的要素，但往往會使我們將目光只放在成功廠商，而忽視廠商退出竹科的現象，又或者未正視高科技產業的特質之一：高風險，因此本研究將試圖運用事件史分析來捕捉在竹科特殊的產業生態中，高科技產業其風險的真正面貌，並運用資源基礎、資源依賴以及組織生態學的觀點來探討竹科的不同廠商所涉風險之影響因素。 / The Hsinchu science park has made remarkable contributions to Taiwan’s development, so far as statistics in 2006, the annual sales volume takes up 35% of the national industrial production volume, nearly 10% of Taiwan’s GDP, it also accounts for 8% of the national export trade. The employment of the Hsinchu science park takes up 1.2% of the total employment of Taiwan. Its significant importance is easy to be understood fully at a glance, so the survival of firms in the Hsinchu science park interweaved with Taiwan’s society and development. Firm exit not only makes the working opportunity deficient, but also affect the usage of policy resources and the socio-economic development of Taiwan. Academic researches about the Hsinchu science park only emphasized the successful element, placed sight on the successful manufacturer, and ignored the phenomenon that some firms have exited from the Hsinchu science park. Actually, one characteristic of the Hi-Tech industry was high risk. So this research will attempt to use the event history analysis to realize firm survival in the Hsinchu science park, catch the real risk of Hi-Tech industry and understand the important factor that effect firm exit from the Hsinchu science park through resource-based theory, resource dependency theory, and organizational ecology perspective.