Sexual minority men are at an increased risk for negative outcomes, including mental health disorders, suicide, substance abuse, and sexual risk behaviors. Internalized Homophobia (IH), roughly defined as sexual orientation-related self-hatred among gay men, has been linked to these outcomes. Since its publication in 1983, the predominant measure of IH used in psychological research has been the Nungesser Homosexual Attitudes Inventory (Nungesser, 1983). The scale is potentially dated, and there is a relative paucity of investigation into its psychometric properties; findings derived through its use may be in question. The current effort describes two studies designed to address these concerns. Study I includes a principal components analysis of the scale using data obtained from an internet sample (N = 486), resulting in suggested revisions for the broader scale, and proposed brief versions of the Self and Disclosure subscales. Study II used data obtained from a second internet sample (N = 884) to further evaluate scale structure and properties. Analyses include confirmatory factor analyses of the original scale, Shidlo's revised version (1994), the suggested alternative, and the Brief Self and Disclosure scales proposed in Study I. Of the three versions of the overall scale, the suggested alternative proposed in Study I exhibited the most favorable fit and highest item loadings. Internal consistency for the suggested alternative was equal to that of the larger NHAI and Shidlo-revised scales. External validity was evaluated through correlations with mental health and suicide, substance use, sexual risk, and orientation-based victimization. Strong results in the expected direction were found only in the instance of mental health, with negative attitudes towards homosexuality being associated with increases in depression and anxiety scores as measured by the Hospital Anxiety and Depression Scale. The suggested scale alternative and Brief Self and Disclosure scales performed similarly to the more extensive NHAI and Shidlo-revised scales, leading to a recommendation for their use in research. Finally, findings from the current effort are discussed in relation to the broader social context impacting the lives and development of sexual minority men. / Psychology

This dissertation contains three essays on the non-pecuniary preferences pertaining to financial asset characteristics and their implications for asset pricing. The first essay considers the pricing implications of screens adopted by socially responsible investors. A model including such investors reconciles the empirically observed risk-adjusted sin-stock abnormal return with a systematic “boycott risk premium” which has a substantial financial impact that is, however, not limited to the targeted firms. The boycott effect cannot be displaced by litigation risk, a neglect effect, and liquidity considerations, or by industry momentum and concentration. The boycott risk factor is valuable in explaining cross-sectional differences in mean returns across industries and its premium varies directly with the relative wealth of socially responsible investors and with the business cycle. The second essay generalizes Fama (1996)’s concept of Multi-Factor Efficiency without being limited by additional random state variables that must affect future investment opportunities. Incorporating non-pecuniary preferences into a representative investor’s utility function generates multi-factor pricing implications. A representative investor chooses among expected returns, variances, and levels of characteristics according to their taste, which gives rise to an N-fund separation theorem with static characteristics. If a portfolio is built to maximize the exposure to the asset characteristics, the covariance between asset returns and this portfolio returns will be identical to the underlying characteristics. Such identity makes obsolete any attempts to distinguish between characteristics and risk exposures as the driving forces behind the cross-sectional variation in stock returns. The third essay develops a procedure for deriving systematic factors from characteristics, based on maximizing each factor’s exposure to a characteristic subject to a given level of factor variance. The resulting characteristic-mimicking portfolios (CMP) price mean asset returns identically as the original characteristics, irrespective of the underlying model. Accordingly, differences in the performance of mimicking factors and characteristics in explaining mean returns should be interpreted as an artifact of arbitrary procedural choices for generating mimicking factors. Factors and characteristics may be distinguished usefully only by determining if CMPs have significant explanatory power for the time series of returns. / Thesis / Doctor of Philosophy (PhD)

Winter Storm Uri damaged parts of the United States, Mexico, and Canada in February of 2021. The State of Texas was heavily affected due to the institutional failure of Texas's primary power provider, the Electric Reliability Council of Texas (ERCOT). Despite similar previous storms that exposed weaknesses in the state's power grid system in 1999 and 2011, ERCOT did not make the necessary changes to prevent a future disaster. The purpose of this study is to advance the understanding of the concept of recreancy through the exploration of eight different dimensions of the concept: trust or distrust in institutions; institutional responsibility for disaster preparedness; responsibility for impacts of a disaster; effectiveness or ineffectiveness of institutions in responding to a disaster; an institution's capability of preventing a similar event in the future; an institution's willingness to make changes in their actions or behavior; confidence that an institution will prevent a similar event in the future; and responsibility for compensation for impacts of a disaster. To examine the composition of the concept of recreancy, I analyzed survey data collected in Texas during April and May of 2022. I aggregated and coded survey data according to the level respondents reported to agree with the survey indicators measuring dimensions of recreancy. I utilized Confirmatory Factor Analysis to analyze if the derived dimensions of recreancy measure recreancy, and if some are more salient than others. Confirmatory Factor Analysis revealed variability in the importance of different dimensions of recreancy, suggesting that some dimensions are more salient than others in shaping residents' perceptions of recreancy in the context of Winter Storm Uri. Further analysis revealed a preliminary model to operationalize recreancy, however further analysis is needed. / Master of Science / In February 2021, Winter Storm Uri devasted regions of the United States, Mexico, and Canada. The state of Texas experienced significant storm impacts due to the failure of its primary power provider, the Electric Reliability Council of Texas (ERCOT). ERCOT is responsible for overseeing and managing the state's power grid. Similar storms in 1999 and 2011 revealed weaknesses in the power grid's infrastructure—state officials mandated but did not require weatherization precautions to prevent future grid failures. ERCOT did not implement the suggested changes and the power grid failure during Winter Storm Uri left millions of Texas residents without access to power, heat, water, and other necessary services. This thesis explores residents' perceptions of ERCOT's institutional failure—recreancy—and aims to understand the concept of recreancy through the examination of eight dimensions: trust or distrust in institutions; institutional responsibility for disaster preparedness; responsibility for impacts of a disaster; effectiveness or ineffectiveness of institutions in responding to a disaster; an institution's capability of preventing a similar event in the future; an institution's willingness to make changes in their actions or behavior; confidence that an institution will prevent a similar event in the future; and responsibility for compensation for impacts of a disaster. I analyzed survey respondents' levels of agreement with each dimension and utilized Confirmatory Factor Analysis to assess the relative importance of the dimensions and if they accurately capture recreancy.

No / While there are many mythical stories of various kinds about the Phoenix it retains several features throughout all of them. In ancient Egypt, the Phoenix was the prodigy of the sun god Ra and appeared in the shape of a giant bird of fire, which was one of the most beautiful creatures on earth. It was remarkable in that it could not foster any offspring and at the end of its life would explode in a ball of fire. Out of the ashes, an egg is formed which then hatches the Phoenix again in its young form. The cry of a Phoenix was supposed to be of miraculous beauty. This chapter will explore if the Phoenix is a suitable metaphor for the recent re-emergence of the US National Science Advisory Board for Biosecurity (NSABB), which was tasked with providing scientific expertise to the government on questions of the security risks of emerging science and technology in the life sciences. The analogy to the Phoenix suggests itself because the NSABB, chartered in 2004, had been inactive for over two years and only recently took up its work. The comparison between the Phoenix and the NSABB gives rise to several questions: first, has the re-emergence of the NSABB been met with an equally beautiful cry of joy among the scientists and security experts? Second, what happens when the Phoenix lies dormant? And third, what took place before the Phoenix was created?

Understanding the lifetime behavior of their products is crucial to the success of any company in the manufacturing and engineering industries. Statistical methods for lifetime data are a key component to achieving this level of understanding. Sometimes a statistical procedure must be updated to be adequate for modeling specific data as is discussed in Chapter 2. However, there are cases in which the methods used in industrial standards are themselves inadequate. This is distressing as more appropriate statistical methods are available but remain unused. The research in Chapter 4 deals with such a situation. The research in Chapter 3 serves as a combination of both scenarios and represents how both statisticians and engineers from the industry can join together to yield beautiful results. After introducing basic concepts and notation in Chapter 1, Chapter 2 focuses on lifetime prediction for a product consisting of multiple components. During the production period, some components may be upgraded or replaced, resulting in a new ``generation" of component. Incorporating this information into a competing risks model can greatly improve the accuracy of lifetime prediction. A generalized competing risks model is proposed and simulation is used to assess its performance. In Chapter 3, optimal and compromise test plans are proposed for constant amplitude fatigue testing. These test plans are based on a nonlinear physical model from the fatigue literature that is able to better capture the nonlinear behavior of fatigue life and account for effects from the testing environment. Sensitivity to the design parameters and modeling assumptions are investigated and suggestions for planning strategies are proposed. Chapter 4 considers the analysis of ADDT data for the purposes of estimating a thermal index. The current industry standards use a two-step procedure involving least squares regression in each step. The methodology preferred in the statistical literature is the maximum likelihood procedure. A comparison of the procedures is performed and two published datasets are used as motivating examples. The maximum likelihood procedure is presented as a more viable alternative to the two-step procedure due to its ability to quantify uncertainty in data inference and modeling flexibility. / Ph. D.

Climate change is exacerbating natural disasters, and extreme weather events increase with intensity and frequency. This requires an in-depth evaluation of locations across the various U.S. climates where natural hazards, vulnerabilities, and potentially damaging impacts will vary. At the local building level within the built environment, private residences are crucial shelter systems to protect against natural disasters, and are a central component in the greater effort of creating comprehensive disaster resilient environments. In light of recent disasters such as Superstorm Sandy, there is an increased awareness that residential buildings and communities need to become more resilient for the changing climates they are located in, or will face devastating consequences. There is a great potential for specific high-performance building technologies to play a vital role in achieving disaster resilience on a local scale. The application of these technologies can not only provide immediate protection and reduced risk for buildings and its occupants, but can additionally alleviate disaster recovery stressors to critical infrastructure and livelihoods by absorbing, adapting, and rapidly recovering from extreme weather events, all while simultaneously promoting sustainable building development. However, few have evaluated the link between residential high-performance building technologies and natural disaster resilience in regards to identifying and prioritizing viable technologies to assist decision-makers with effective implementation. This research developed a framework for a process that prioritizes residential building technologies that encompass both high-performance and resilience qualities that can be implemented for a variety of housing contexts to mitigate risks associated with climate induced natural hazards. Decision-makers can utilize this process to evaluate a residential building for natural disaster risks, and communicate strategies to improve building performance and resilience in response to such risks. / Ph. D.

No / The importance of a collaborative approach between the project team, end-users, and stakeholders in managing complex decisions and risks in project environments has long been emphasized. The Porter model emphasizes the need to focus on client needs and competitive advantage. However, a lack of resources and capability development may hinder the project team's ability to provide appropriate services. Supervisors, team members, and end-users can play a supportive role in easing complexity in risk management and decision-making. It is important to understand standards as performance measures for decision-making and the need for detailed knowledge of the project brief. The value of group decision support systems and low-intensity involvements in decision-making would give rise to involving end-users in critical decision-making, the importance of focusing on organizational culture and strategic planning, and the need for a change of mindset to align individual perceptions with the norm. It is also important to gather and analyze information before making a decision. While some project teams see end-users as a threat to their judgment, the research emphasizes the duty to respond to end-users' needs and highlights the value they add to risk assessment.

Social media platforms have become a popular and inexpensive way for people to communicate with millions of others. However, this increased usage has also led to an increase in risks associated with it, such as cyberbullying, trolling, misinformation, and privacy abuse. Previous research in this field has mainly focused on isolated aspects of online risk detection, which can limit the effectiveness of these studies. To address these issues, this dissertation presents a more holistic approach to detecting and reducing harmful and abusive behavior online. To gain an initial understanding of the problem, we first present a mixed-method study of messages and media files shared in private conversations by youth to understand the risky communication experienced by them. We use these findings to determine which features can automatically detect unsafe private conversations and whether social media platforms can implement such a system given the recent move towards end-to-end encryption. We present an ensemble machine learning classifier to detect risks in private messages and how to incorporate child safety by design. In the second part of this thesis, we will explore ways to stay ahead of hate and toxicity, given the changing online behaviors. Toxic language changes over time, with aggressors inventing new insults and abusive terms that frequently target certain vulnerable communities, including women and minorities. We develop automated systems that, given an initial lexicon of toxic speech, can learn new and emerging toxic words by observing conversations on social networks. Lastly, we examine the cross-platform implications of employing risk detection systems online. Most of the research focuses only on malicious activity that occurs on one platform, which does not allow us to get a full picture of the problem. Users are obviously not bound to a single platform but can migrate to other online services for example, anecdotal evidence shows that once hateful users are banned from Twitter, they often move to Gab, an alternative social network with an open lack of moderation marketed as protection of "free speech". Consequently, we argue that moderation efforts should extend beyond safeguarding users on individual platforms and account for the potential adverse consequences of banning users from prominent platforms.

Yes / We provide a generalized analytical methodology for evaluating a real sequential investment opportunity, which does not rely on a multivariate distribution function, but which allows for stage-specific risks and drifts. This model may be a useful capital budgeting and valuation tool for exploration and development projects, where risks change over the stages. We construct a stage threshold pattern whereby the final stage threshold exceeds the early stage threshold due to drift differentials between the project values at the various stages, value volatility differences, and correlation differentials, implying a rich menu of parameter values that may be suitable for a variety of projects. Governments seeking to motivate early final stage investments might lower final stage project volatility or specify project value decline over time, unless prospective owners are willing to pay the real option value (ROV) for concessions. In contrast, concession owners, more interested in ROV than thresholds that motivate early investments, may welcome final stage value escalation, or guarantees that reduce the correlation between project value and construction cost.

Yes / Government organisations have been shifting to cloud-based services in order to reduce their total investments in IT infrastructures and resources (e.g. data centers), as well as capitalise on cloud computing’s numerous rewards. However, just like any other technology investments there are also concerns over the potential risks of implementing cloud-based technologies. Such concerns and the paucity of scholarly literature focusing on cloud computing from a governmental context confirm the need for exploratory research and to draw lessons for government authorities and others in order to ensure a reduction in costly mistakes. This paper therefore investigates the implementation of cloud computing in both a practical setting and from an organisational user perspective via three UK local government authorities. Through the qualitative case study enquiries, the authors are able to extrapolate perceived rewards and risks factors which are mapped against the literature so that emergent factors can be identified. All three cloud deployments resulted in varying outcomes which included key rewards such as improved information management, flexibility of work practices and also posed risks such as loss of control and lack of data ownership to the organisations. These findings derived from the aggregated organisational user perspectives will be of benefit to both academics and practitioners engaged in cloud computing research and its strategic implementation in the public sector.