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Hidden Power in Formalized Structures

2024-05-14 , Choi, Jeongwon

My dissertation examines resource allocation across organizations as a policy outcome. I argue that the hidden power of organizations behind the formalized institutional setting predicts the resource allocation outcomes. The power I look at is generated from inter-organization resource dependency (power-dependency), as described by Resource Dependence Theory (RDT). In my dissertation, I demonstrate how the power-dependency is institutionalized and operates in a formalized institutional structure, affecting the resource allocation outcomes beyond the formal rules of a policy. I use the case of the US federal system of Facilities & Administrative (F&A) cost reimbursement to universities. The system has governed the resource exchange of federal funding for the university’s production of science since the 1940s. The F&A cost reimbursement is exchanged for the overhead costs used for the university’s federally sponsored research. The rules and processes of the reimbursement are highly formalized. The federal government spends more than $10 billion for indirect cost reimbursements, with huge variation in reimbursement rates across research universities, ranging from 40 percent to 70 percent, where 1 percent can equal millions of dollars. This variation has ignited longstanding debates about why some organizations appear to fare much better than others in this highly formalized institutional setting. My dissertation asks where this variation comes from. I begin by developing the history of the F&A system and show how inter-organization power structures have created, sustained, and modified the system in a way that allows the workings of power (Ch. 2). I then find that inter-organization power asymmetry and mutual dependence from resource interdependency predict variation in F&A cost reimbursement rates across universities, leading to unequal resource allocation outcomes (Ch. 3). I also find indirect power of universities over agencies through Congress moderates power asymmetry between universities and agencies, and hence also affects the inequality in F&A rates (Ch. 4). My research depicts a holistic view of power-dependency affecting organizations’ access to resources by showing the workings of power at different levels (bilateral, triangular, and institutional settings). The dissertation contributes to the movement in organization and management studies to revitalize RDT. The research expands the scope of RDT to a formalized setting where there should be less discretion in resource allocation and specifies conditions for the workings of power, thereby enhancing RDT’s generalizability. I also develop RDT by modeling indirect power based on formal authority relations and integrating it with the direct exchange power structure. I discuss agency-contingent differences in the workings of direct and indirect power in a formalized setting, highlighting the government as an exchange partner that responds to power-dependency. I examine structural characteristics of power-dependency, making explicit the power effects hidden in a formalized setting.

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Public Use of Open Access Research: Evidence from the National Academies and Harvard DASH Repository

2023-08-09 , Doshi, Ameet

Once only available to those with university or scientific affiliations, the peer-reviewed literature is increasingly globally accessible to anyone with internet access. Over the past 20 years, this “open access” (OA) movement has transformed publishing business models, and changed the ways scholars use and cite research. However, given this unprecedented level of access to scientific and technical information, do non-researchers, or lay persons, who are not steeped in the foundational knowledge of a field use this information? Specialist knowledge requires effort by the general public to understand (Epstein, 1996; Savolainen, 1995; Shen, 1975). What motivates people to overcome obstacles to find and synthesize scholarly research into their everyday lives? The proposed research seeks to better understand this phenomenon in an emerging era of open access to science. There is an increase in government mandates to make publicly-funded research open (for example: NIH Open Access policy, OSTP Public Access Plan, EU Plan S). These mandates implicitly and explicitly assume that non-researchers desire access to, and can make productive use of, scientific literature. Thus, the question of how the public uses open access scholarship is a policy relevant inquiry worthy of study. As more journals offer (sometimes costly) OA options for publication in response to institutional mandates we can anticipate continued growth of openly accessible peer-reviewed science. Yet evidence is lacking about why non-researchers seek, read and integrate OA into their lives. Generally, there is a need to better understand open access use from the public’s perspective. This is a policy relevant area of inquiry since federal and international mandates are changing the way research is published, ostensibly to expand access to a wider array of society. Yet very little empirical work exists to understand if, and why, non-researchers use open access research. My thesis aims to fill this gap.

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Essays in Education Policy Analytics: Prediction of At-Risk Students, International Mobility, Cognitive Trade-Offs

2023-03-21 , Zullo, Matteo

The dissertation includes three essays contributing to our understanding of human capital development and student talent allocation. The first essay provides insights into the impact of algorithmic student advising programs, while the second essay highlights the role of higher education agencies in promoting international student mobility. The third essay evaluates the cognitive development trade-offs entailed by technical coursework. The first essay discusses the Graduation and Progression (GPS) program, which is an algorithmic student advising platform implemented by Georgia State University. The study analyzes the impact of this program on student course-taking by comparing GPS-advised students with those who did not receive advising. The study failed to credit the program to have increased graduation rates by improving academic fit but found that marginal students tended to leave college earlier. Also, the study provides evidence of assortative matching between students and course selection, albeit only for STEM Computational majors. The second essay examines the relationship between the 1996-2016 expansion of the German agency DAAD's outbound offices and international student enrollment in Germany. The findings suggest that an increase in the number of DAAD offices has a positive impact on international student enrollment in Germany, and that the first office foundation has the largest effect. The study concludes by discussing the policy implications of these findings for countries competing in the global race for talent. The third essay evaluates cognitive development trade-offs between numeracy and literacy skills. The study uses PISA data and analyzes the educational and financial gains from technical education versus the potential underdevelopment of verbal skills. The study finds that the technical track outperforms the Liberal Arts track due to greater educational production efficiency, which overcompensates for worse educational production inputs. The findings suggest that the STEM advantage is linked to the four additional instructional units in math and physics, and that there are no secondary effects due to differences in preexisting levels of student skills.

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A QUANTITATIVE ANALYSIS OF OWNERSHIP-INDUCED QUALITY GAPS IN THE LONG-TERM CARE SECTOR: INFLUENCES OF OWNERSHIP CONVERSIONS, SELF-REPORTING, REGULATORY REFORMS, AND THE COVID-19 PANDEMIC

2022-08-01 , Coskun, Muhammet Emre

This dissertation presents a quantitative analysis of the association between ownership types and quality of services in the long-term care sector in the United States. The study employs dynamic difference-in-differences models to investigate the effects of for-profit ownership conversions on nursing home quality indicators by drawing on national-level panel data for the years between 2013 and 2021. Additionally, the adverse effects of information asymmetries are examined by comparing changes in government-inspected quality measures with changes in self-reported quality measures following a for-profit conversion of a nursing home. Furthermore, the impact of the recent regulatory changes implemented at the end of 2016 in the nursing home sector and the facility-level factors associated with the COVID-19 pandemic outcomes in nursing homes are examined with respect to the quality trends and differences in quality by ownership types. Lastly, this study explores the relationship between ownership and quality in assisted living facilities in the State of Georgia using state inspection data. Overall, this dissertation finds that for-profit ownership status is associated with worse quality outcomes among nursing homes and assisted living facilities, including adverse outcomes of the COVID-19 pandemic. Moreover, the analyses show that the recent regulatory reforms had little to no effect on improving the quality of nursing homes over time. The findings are discussed to help policymakers formulate new policies and effective regulations to improve the quality of long-term care.

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Navigating the Privacy Landscape of Large Language Models: Challenges, Technologies, and Policy Directions

2024-05-05 , Kelklie, Moges

Data privacy has become a key concern of large language models(LLMs), both in the large trove of information they can infer and in the inherent inflexibility of models in forgetting the learned data. LLMs do not have an easy way to delete information; sensitive data could be inferred through prompt engineering, thus raising concerns about data privacy. This article attempts to address the challenge of LLM data privacy and how policy can help mitigate some of the privacy concerns.

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Scoping Environmental Technologies: Learning from Life Cycle Assessment and Policy Adoption

2023-07-25 , Banboukian, Aline

In this dissertation, I use life cycle assessment (LCA) and policy adoption theory to evaluate multi-faceted environmental technologies for environmental policy development in the agriculture and water sector. This dissertation expands on existing research by providing empirical evidence and insights using LCA and policy adoption assessment. This dissertation highlights two ways to evaluate new multi-faceted environmental technologies, both providing input that supports improved and revised understanding of how technologies and policies can be re-framed for potential benefit. The first study is a systematic literature review of the use of LCA in environmental policy. I find that the studies have largely been published since 2013, and focus on greenhouse gas emissions and climate impacts. There are few policy experts publishing in this area. The literature on LCA in policy highlights the ability of LCA to provide scientific measurable information for policy options and compare between different alternatives. Additionally it highlights LCA’s ability to provide insight on the hotspots for sound sustainable decision making. The negative discussion on LCA in policy focuses on information that LCA cannot capture. To overcome the barriers of using LCA in policy, suggestions are to ensure the right type of LCA is chosen for the policy, or that other models are coupled with LCA to provide all the necessary details needed for the policy. The main policy processes these publications address are policy framing and policy evaluation. Studies 2 and 3 provide an LCA of (1) different agricultural systems, and (2) integrated wastewater treatment plant technologies coupled with agricultural systems, in a comprehensive analysis of the environmental impacts of each of the multifaceted technologies. The overall study is an LCA of wastewater reuse for agriculture; I developed the assessment in two separate chapters due to the multiple technologies and factors involved. These chapters show that the lifecycle greenhouse gas impacts of controlled environmental agriculture dominate environmental impacts, although in other impact categories it has lower environmental impacts than open-field and low-energy-greenhouse agriculture. Water reuse can substantially reduce water consumption impacts of some types of agriculture. Substantial reduction in energy consumption of controlled environment agriculture, and substantial improvements in the efficiency of municipal water use would allow environmental benefits to be derived from reuse of both water and nutrients for agriculture. Finally, study 4 uses policy adoption assessment to examine the drivers of water reuse policy adoption. Internal determinants and regional motivators are investigated. I find that water reuse does not face the challenges of political ideology that have been observed in other types of sustainability policies. I find that water reuse policy adoption is responsive to local and regional challenges such as drought, and to the interests of environmentalists, farmers, and water consumers. This dissertation addresses the use of life cycle assessment (LCA) and policy adoption assessment for policy development for new multi-faceted technologies, such as those linking food, energy, and water. The combination of LCA and policy adoption assessment can provide policymakers and scholars with an understanding of both what the environmental impacts are and what factors motivate their adoption in policy.

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The Mobilization of Social Networks in Professional Development Decision-Making – A Mixed-Methods Study in a Technical Field

2022-08-02 , Ruthotto, Isabel

THE MOBILIZATION OF SOCIAL NETWORKS IN PROFESSIONAL DEVELOPMENT DECISION-MAKING –A MIXED-METHODS STUDY IN A TECHNICAL FIELD Isabel Ruthotto 171 pages Directed by Dr. Julia Melkers Vast technological innovations have been transforming labor markets and workplaces. Against this background, identifying ways to foster a skilled and resilient technical workforce and determining what role industry, higher education institutions, and policymakers play in this regard has become a core concern of political and societal debates. The dissertation contributes to this discourse by looking at how adults working in tech decided to invest in skill development and professional advancement through the pursuit of an online graduate degree in computer science. The dissertation seeks to understand whether, when, and how social networks influenced this decision process. The focus on networks is important since it addresses a distinct gap as to how decision-making has traditionally been conceptualized. The results support the central argument that the decision to pursue an online graduate degree is seldom an internal, autonomous thought process, but is often shaped by social relationships through consultation, advice, and support. Family members, friends, coworkers, supervisors, and acquaintances all matter in this process – albeit to varying extents and in different capacities. A complex set of individual and contextual factors influence the broad range of social support-seeking during decision-making. The results validate the importance of examining professional development choices in social contexts, offer several theoretical and policy implications, and open avenues for future research.

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Three Essays on Skills and Individual Decision-Making

2023-12-10 , Churkina, Olga

The dissertation examines the concept of skills, and and their impact on charitable giving behavior, labor market outcomes, and marital choices. The first essay conducts a controlled laboratory experiment, investigating the relationship between worker performance and their pro-social behavior in the context of charitable contributions. The second essay estimates the employment premium associated with online certificates in data science through a randomized field experiment. The third essay expands on a multi-period microeconomics model of educational and marital choices in developing countries. The outcomes of this study address questions that are shared concern for the academic community and policy-makers.

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Who Owns America? A Methodology for Identifying Landlords’ Ownership Scale and the Implications for Targeted Code Enforcement

2023-05 , An, Brian Y. , Jakabovics, Andrew , Orlando, Anthony W. , Rodnyansky, Seva , Son, Eunjee

Scholars and practitioners are increasingly interested in understanding who owns real estate in communities and resultant implications for targeted planning approaches. Yet, practitioners lack an efficient and comprehensive methodology to assess landlords’ ownership scale, namely how many properties they own in a given geographic area. The existence of variegated ownership, multiple legal entities, siloed databases within government bureaucracies, and inconsistencies in spelling and documentation across data entries make it time-consuming and costly to determine the extent of real estate ownership by the same landlords. To address these challenges, this study provides a data-driven natural language processing solution. Using OpenRefine, an open-source software, we present a step-by-step, practice-oriented methodology for amassing data, cleaning textual inconsistencies, and clustering properties to uncover the truer ownership scale in local housing markets. Applied to a large U.S. urban county—Fulton, home to Atlanta, Georgia—our proposed methodology demonstrates its superior efficiency, comprehensiveness, and accuracy, compared to traditional approaches. Using code enforcement as a study frame, we then empirically examine a linkage between landlords’ ownership scale and their code violation patterns. With the proposed methodology in place, the analysis consistently shows that the ownership scale is related to both the likelihood and number of code violations. In contrast, the analysis misses such a critical linkage without applying the methodology. Our methodology yields practical implications regarding targeted code enforcement.

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Science Gone Wrong: Understanding scientific work by examining "failures" across productions, consumptions, and careers in science

2022-08-01 , Woo, Seokkyun Joshua

This dissertation examines “failures” across three different dimensions of the production of science (production of data, impacts, careers) to further expand our understanding of scientific work, thereby providing effective implications for science policy. The first study (Chapter 2) involves ethnographic observation of the work of bench scientists at material science labs to understand the problem-solving activities involving frequent interruptions in producing experimental data. The second study (Chapter 3) expands our understanding of citation practice in scholarly communication. In doing so, I examine citations to retracted references to test existing theories and propose an additional mechanism for how scientists embed other scientists’ works into their papers. The last study (Chapter 4) addresses the long-standing issue of gender inequality in scientific careers. In doing so, I ask how the increasingly bifurcated production role in science may shape career longevity and how this relationship may differ between women and men scientists. Together, these studies use a sociology of work perspective to better understand various components of the production of science in order to develop a deeper understanding of the science of science as well as to inform policy debates and other initiatives designed to improve the production of science.

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