Sexual satisfaction is a major component of human behavior. Individuals in relationships have specific demands for sexual satisfaction. Relationships and societal trends may impact the standards for sexual performance. The effects of performance can result in negative transitions in relationships. Therefore, Individuals may also consider outside variables in addition to relationship status, length of relationships, sexual orientation, gender-role, and religiousness. This poster presentation will be based on a literature review. The review reveals positive effects of religiousness on sexual satisfaction for those married more than ten years. In comparison with social behaviors, gender-roles are not influenced by traditional or non-traditional beliefs. When social norms and sexual orientation are paired in correlation with satisfaction in relationships, gay men and lesbians rate higher than heterosexuals in the area of sexual satisfaction. When long-term and short-term relationships are measured based on sexual satisfaction, results indicate long-term relationships are successful due to active communication and no sexual dysfunctions.

Infant and Early Childhood Mental Health (IECMH) providers engage in uniquely relational work with high-risk families that expose them to the full advantages (i.e., compassion satisfaction [CS]) and disadvantages (e.g., burn-out [BO]) of a helper role. Though the pandemic seemed poised to escalate disadvantage, most early pandemic studies found high CS alongside elevated BO. Unfortunately, as COVID-19 has continued, CS has declined while BO has increased. Given the delayed COVID-19 impact on children, these changes may be particularly acute for IECMH providers. Using a longitudinal cohort of 27 IECMH providers, this study aimed to describe and quantify changes in professional wellbeing and contributing factors over a 12-month period (T1 – T12) from early to mid-pandemic. Little changed from T1 to T12 for IECMH provider CS (M = 41.33 vs. M = 41.08) or BO (M = 22.22 vs. M = 22.65) scores. Variables known to contribute to CS similarly held when T1 was compared to T12, but they fluctuated considerably and non-linearly between these time points. Variable relationships with CS also changed over time necessitating an adjusted hierarchal regression model. This model accounted for 20% of variance in T12 CS. Pandemic experiences like loss are reported; needs/supports are summarized using content analysis. Results underscore the importance of cohort, multi-time point design and the need for non-linear analysis to contextualize the interplay of shared and individual experiences within COVID-19. Implications for maintaining IECMH professional wellbeing moving forward and improving the health of other fields are discussed.

The history of transportation planning in New York City has created disparities between those who have sufficient access to the public transportation network, and those who face structural barriers to traveling from their home to education, employment, and healthcare opportunities. This thesis analyzes the legacy of discriminatory policy surrounding the Metropolitan Transportation Authority (MTA) and city and state governments that have failed to support vital infrastructure improvement projects and service changes to provide multi-modal welfare to New York’s working poor. By exploring issues of transit equity as they pertain to the New York City subway system, this thesis raises the question: which communities lack adequate access to public transit opportunity and what are the policies and historical developments that have created these inequities? Through examination of grassroots community-based movements towards social justice and transportation equity, this thesis will review the proposals, campaigns, and demands that citizen-driven organizations have fought for in New York City. These movements, I argue, are the most effective method to achieve greater transportation justice and intergenerational equity.

The U.S. is the only OECD country that does not offer any form of federal paid parental leave. Only three states—California, New Jersey and Rhode Island—have state-provided paid leave policies; implemented in 2004, 2009 and 2014, respectively. Through descriptive statistics and difference-in-difference-in-difference regression analyses of the wages of women and men of childbearing age (19-45 years) in those three states, we assess whether the paid leave programs have effected wages, and whether these effects vary depending on gender. Our results show that wages of women of childbearing age saw negligible net effects post-policy in policy states, although statistically insignificant. On the other hand, the wages of men of childbearing age saw improvements post-policy implementation in policy states, compared to wages in non-policy states. Although the policies do not necessarily widen the gender wage gap, they do not work to help close it, due to flaws in the policies. To be more effective in reducing gender wage gaps, these policies need to increase the amount of paid support, and implement job protection rights in order to decrease the opportunity costs of men taking leave. If more men are able to take paid leave, then potentially parts of the gender wage gap that are due to employers viewing women as less attached to the workforce can decrease. Through this research we came to important conclusions that highlight the ways in which support of working parents in the US is lacking, and offered recommendations to create more equitable and effective policies.

This senior thesis is an examination of the major complexities and considerations encountered in developing an e-learning program. In light of the changing landscape of higher education resulting from technological advancement, combined with changing pedagogies and financial pressures, traditional institutions are under heightened scrutiny and most in need of innovation. Online learning as been proposed as a solution to many of these issues, but creating a successful program is no small feat. Furthermore, experimental research on specific course designs and delivery often fails upon real-world implementation. Looking through the lens of Design-Base-Implementation Research (DBIR), an emerging research model that seeks to rectify this inefficiency, this thesis will first affirm the crucial need for active leadership throughout the development and implementation process. Analysis will then turn to the most pertinent elements administrators must address, including the motivations and catalysts for innovation, funding, faculty engagement, IT support, course design and project evaluation; in keeping with DBIR methodology, each of these considerations will take different forms and require alternative courses of action based on the unique institutional attributes and circumstances. Finally, the exploration will culminate in reasserting the urgency for innovation in higher education, and concluding that a uniform “solution” will not only be pragmatically impossible but also detrimental to both institutional legacy and student education: a quality and sustainable program necessitates due diligence in acknowledging and working with the distinct characteristics of each institution.

This thesis is serves to examine the refugee policies in Tanzania and Uganda and how they have affected refugee participation in their labor market economies. I focused on two developing nations because much of refugee discourse revolves around the global north, leaving developing nations out of the conversation. This gap in discourse inspired this topic in hopes of encouraging more scholarly contributions. Considering the economic impact of refugees provides an empirical approach to humanitarian issues exposing the overlap between politics, economics, and humanity.

Ce mémoire de maîtrise porte sur les algorithmes de « data mining » et de « machine learning », constitutifs d’un domaine que l’on appelle plus récemment la « science des données ». Pour essayer d’éclairer la portée et la spécificité des enjeux que leur usage soulève dans nos sociétés, il est proposé d’interroger le rapport qu’ils entretiennent avec les fondements et les limites des outils plus traditionnels de la statistique sociale/mathématique, bien documentés en sociologie, à l'égard notamment du « langage des variables » et du raisonnement expérimental « toutes choses égales par ailleurs ». En inscrivant l’approche au croisement de la sociologie de la connaissance et de la quantification, le cadre conceptuel s’inspire de l’épistémologie comparative de Gilles-Gaston Granger, de la « méta-épistémologie historique » de Ian Hacking et de la sociohistoire de la statistique sociale d’Alain Desrosières. Par l’idée de mises en forme algorithmique de la vie sociale, les algorithmes de calcul sont envisagés comme modes d’investigation, partiellement ou complètement automatisés, procédant à des mises en forme et en ordre plurielles et différenciées du social et de ses propriétés. À partir de données de Statistique Canada servant à étayer plus concrètement les formes de connaissances produites et les visées d’objets qu’elles délimitent en termes de possibilités et de contraintes d’expérience, la présente étude de cas entreprend d’examiner le clivage des méthodes « classiques » et « contemporaines » à l’intérieur du cadre supervisé de l’apprentissage. Pour ce faire, trois techniques/familles d’algorithmes sont comparées sous l’angle de leurs opérations d’analyse: 1) les méthodes de régression logistique, 2) les arbres de décision et 3) les forêts aléatoires. L’objectif de cette analyse sociologique théorique comme empirique est d’examiner comment ces approches opèrent certains modes de classification et facilitent ou défavorisent des représentations du monde et de l’individu. Le travail conduit plus généralement à ouvrir quelques pistes de réflexion quant aux rapports de compatibilité et d’incompatibilité des formes de raisonnement du style statistique et probabiliste avec certains états du développement de la sociologie. / This master's thesis focuses on data mining and machine learning algorithms, constituting a field more recently called “data science”. To try to shed light on the specificity of the issues they raise in our societies, it is proposed to question the relationship they maintain with the foundations and the limits of the more “classic” tools of mathematical statistics in sociology, with regard in particular to the “language of variables” and to the experimental reasoning “all other things being equal” (cetaris paribus). By placing the approach at the intersection of the sociology of knowledge and quantification, the conceptual framework is inspired by the comparative epistemology of Gilles-Gaston Granger (1920-2016), the historical meta-epistemology of Ian Hacking (1936-) and the sociohistory of social statistics by Alain Desrosières (1940-2013). Through the idea of “mises en forme algorithmique de la vie sociale”, computational algorithms are considered as partially or completely automated types of investigation, carrying out plural and differentiated of shaping and ordering of the social and its properties. Using data from Statistics Canada used to more concretely support the forms of knowledge produced as well as the possibilities and experience constraints that they define, this case study sets out to examine the divide between “classical” and more “contemporary” methods of analysis within the framework of “supervised” learning. To do this, three algorithm techniques (or families of algorithms) are compared from the angle of their knowledge operations: 1) logistic regressions, 2) decision trees and 3) random forests. The objective of this theoretical as well as empirical work is to examine how these approaches operate certain modes of classification, facilitate or disadvantage representations of the world and can also be performative in social activities. The research work more generally leads to opening up some avenues of reflection as to the compatibility and incompatibility relationships of the forms of reasoning of the statistical and probabilistic style with certain states of development in society and in sociology.

This study was done to see the effects of a war on the economy and the internal politics of the United States. In selecting the engagement, we would study we agreed the Iraq War would be aided by a large amount of sampling of public opinion that was more nuanced than in previous wars. The Iraq War was a very complicated war, as it was controversial from the beginning and became a political issue while continuing to be a war fought by Americans abroad. Based on the literature, there were many starting effects and assumptions that were accounted for such as the ‘rally round the flag effect.' As a historical landmark, the Iraq War is important for being a significant conflict after the Vietnam War, another very controversial conflict in the eyes of the American public. The hypothesis that I presented were not supported by the data. The impact of the war on the economy was not strong enough that it would create pressure for the sort of model I created to apply. In this model the economic problems faced domestically could lead to more unemployment and therefore to higher military recruitment rates. While this was partially true in 2008, the consequence was not a significantly higher amount of people in the military. Ultimately, this project requires to be done in a more thorough setting where effects may be compared with those of other similar countries in similar scenarios.

During May of 2023, Florida Governor Ron DeSantis signed multiple bills into law, which included House Bill 1521, Senate Bill 1580, and Senate Bill 254. Critics have regarded these bills to directly discriminate against transgender individuals and negatively impact their quality of life. The main research question this project seeks to answer is what impact these bills have, if any, on transgender individuals who live in the state of Florida. This includes experiences that negatively impact quality of life outcomes and mental health disparities. An online survey of a small sample of the population that self identifies as transgender, that had lived in Florida for at least 1 month prior to and after the passing of the bills and were over 18 years old was used. Participants answered 2 sets of questions using a five-point Likert scale. One set asked about feelings and experiences prior to the passing of the bills, and the other after the passing of the bills, which included questions about mental health disparities seen commonly in transgender individuals such as depression, suicidal ideation and more. A comparison of the average Likert scale score prior to and after the passing of the bills showed a 10-20 percent increase in mental health disparities, and a large decrease in perceived ease of access to healthcare and satisfaction with state governmental support. Across the board, increases to negative mental health and quality of life outcomes were seen in our sample, which paints a troubling picture as to how these types of bills impact transgender quality of life and mental health outcomes.

This thesis evaluates the equity performance of a recent state environmental justice policy, California’s Senate Bill 535 (S.B. 535). “Environmental justice” refers to the disproportionate environmental harm imposed on low-income and minority communities. S.B. 535 uses competitive grants to provide funding to these communities. The research is centered around two questions: (1) to what extent has S.B. 535 experienced successful implementation in its first year of operation, and (2) how can policy actors improve implementation while balancing performance and equity goals? In regards to the first question, I utilize a case study of the policy’s implementation within 17 local governments in Riverside County. I find that the number of actors involved and the alignment of their interests prevent the policy from more successful implementation. Local government officials identify staff capacity as a primary concern in the program’s implementation. I then evaluate the policy’s balance of program performance and equity with an econometric analysis that characterizes the decisions of local governments to implement the policy. I find impressive equity performance, as low-income and minority populations are more likely to participate. The implementing governments have sufficient capacity to achieve program goals, as larger cities and cities with more staff per capita are more likely to participate. My findings support the use of competitive grants in environmental justice policies. The S.B. 535 grant program demonstrates the ability to distribute funding to governments with both socioeconomic disadvantage and the capacity for successful implementation. The analysis concludes with policy recommendations.