This research investigates how public organizations interpret and respond to the threats they face. Drawing on the open interpretative framework and progressing through its stages (i.e., data collection, interpretation, and action-taking), the three studies of the dissertation build on each other to examine how US public transit agencies deal with the risks posed by extreme weather events. The first study analyzes the “data collection” stage and draws on information processing theory to investigate how various sources of information shape public agencies’ risk perceptions. Integrating administrative data with a 2019 survey of US transit managers, results show that reliance on scientific sources of information is positively associated with perceived risk of extreme weather events. The effect of contracting on risk perceptions is contingent upon agencies’ outsourcing strategies. The second study expands on the first one and focuses on the “interpretation” stage, examining how organizations cultivate a shared perception of extreme weather events. Analyzing in-depth semi-structured interviews with public managers employed at four transit agencies, the study identifies and describes three processes that foster the development of intersubjective interpretations: conversation, suppression, and shared experiences. Informed by the findings of the first two studies, the third one examines the role played by organizational interpretative processes in enabling the undertaking of adaptive actions. I test my expectations using data coming from a follow-up 2023 national survey of public transit managers. Findings underscore the importance of “debative cooperation” and cross-agency boundary-spanning activities in facilitating the development of shared cause maps and favoring adaptation. Overall, the dissertation provides an integrated and comprehensive investigation of the organizational and social elements that shape effective risk management and adaptation to extreme phenomena.

Street-level bureaucracy (SLB) theory argues that public servants take shortcuts when making decisions about the delivery of public services. These shortcuts can lead SLBs to treat citizens unfairly. Public administration and political science researchers have found some evidence that street-level bureaucrats act in biased ways towards ethnic and racial minorities, citizens of lower socioeconomic status, and religious minorities. I expand on the SLB literature on discrimination by examining whether SLBs discriminate based on the political ideology of citizens. According to the Ideological-Conflict Hypothesis, individuals act in biased ways towards others whose political values conflict with their own. Using the Ideological-Conflict Hypothesis, I test whether SLBs working in local governments discriminate against citizens based on political ideology and whether discrimination is related to type of service delivery (e.g. needs based versus universal). I carry out two audit experiments to test for discrimination. One audit experiment tests for political ideology discrimination in a need-based program among a sample of public housing authorities in the United States (US). The sample is limited to areas where over 60% of citizens voted for the Democratic candidate in the 2020 Presidential Election (n = 274)—and where over 60% voted for the Republican candidate (n = 274). The other audit experiment tests for political ideology discrimination in the delivery of a universal service using a sample municipal parks departments in US cities. The sample is cities with over 25,000 residents where at least 60% of citizens in the county voted for the Democratic candidate in the 2020 Presidential Election (n = 227) and counties where at least 60% of citizens voted for Republican candidate (n = 227). The treatment signals that an email is from a conservative citizen, a liberal citizen, or a citizen with no identifiable political ideology. The results of my dissertation provide some support for the Ideological-Conflict Hypothesis and evidence indicates SLBs discriminate based on political ideology. The results do not find differences in political discrimination for needs-based public service delivery compared to universal public service delivery.

Theories related to social identity provide insight on how gender may be meaningful in organizations. This dissertation examines how psychosocial outcomes for science, technology, engineering, and mathematics (STEM) faculty are influenced by the proportion of women in productivity, support, and advice networks in gendered academic institutions. Psychosocial outcomes are defined as the psychological and social perspectives of the organizational environment. Gendered aspects in organizations are of theoretical importance because they provide opportunities to investigate how STEM faculty attain psychosocial outcomes. An underlying argument in gender literature is that women, compared to men, are more likely to provide emotional support. As women’s presence in STEM departments increases, STEM faculty are likely to rely on women to provide emotional support which may influence psychosocial outcomes of the work environment.

Universities are considered to be gendered organizational environments, where masculine and feminine characteristics are evident within their processes, practices, images, and through distribution of power. Universities are broadly categorized as two types: research focused and teaching focused universities. Both university types are deeply involved with the education of students but promotional standards for faculty members and the primary focus of these universities is dictated by the categorization of research versus teaching. University structuring is gendered, making them an ideal setting to investigate questions related to identity and psychosocial outcomes. Drawing from gendered theory, social identity theory, social network theory, and social capital theory, I ask the following research question: Does the proportion of women in informal networks influence psychosocial outcomes within gendered university settings?

To examine how psychosocial outcomes are influenced by informal networks, I use survey data from a 2011 National Science Foundation funded national survey of STEM faculty across universities in the United States (U.S.). I find that psychosocial outcomes vary by university type, faculty gender, and a high proportion of women in three types of academic informal networks. I conclude with a discussion about what the results mean for practice and future research.

This dissertation consists of three essays, each examining distinct aspects about public organization adaptation to extreme events using evidence from public transit agencies under the influence of extreme weather in the United States (U.S.). The first essay focuses on predicting organizational adaptive behavior. Building on extant theories on adaptation and organizational learning, it develops a theoretical framework to uncover the pathways through which extreme events impact public organizations and identify the key learning mechanisms involved in adaptation. Using a structural equation model on data from a 2016 national survey, the study highlights the critical role of risk perception to translate signals from the external environment to organizational adaptive behavior.

The second essay expands on the first one to incorporate the organizational environment and model the adaptive system. Combining an agent-based model and qualitative interviews with key decision makers, the study investigates how adaptation occurs over time in multiplex contexts consisting of the natural hazards, organizations, institutions and social networks. The study ends with a series of refined propositions about the mechanisms involved in public organization adaptation. Specifically, the analysis suggests that risk perception needs to be examined relative to risk tolerance to determine organizational motivation to adapt, and underscore the criticality of coupling between the motivation and opportunities to enable adaptation. The results further show that the coupling can be enhanced through lowering organizational risk perception decay or synchronizing opportunities with extreme event occurrences to promote adaptation.

The third essay shifts the gaze from adaptation mechanisms to organizational outcomes. It uses a stochastic frontier analysis to quantify the impacts of extreme events on public organization performance and, importantly, the role of organizational adaptive capacity in moderating the impacts. The findings confirm that extreme events negatively affect organizational performance and that organizations with higher adaptive capacity are more able to mitigate those effects, thereby lending support to research efforts in the first two essays dedicated to identifying preconditions and mechanisms involved in the adaptation process. Taken together, this dissertation comprehensively advances understanding about public organization adaptation to extreme events.

This research examines data exchange between city departments and external stakeholders; particularly, why city departments have different capacity to access data from departments in the same city, other public agencies, private and nonprofit organizations. Data access is of theoretical interest because it provides the opportunity to investigate how public organizations and public managers deal with a portfolio of relationships in a loosely structured context characterized by dynamics of power and influence. Moreover, enhancing data access is important for public managers to increase the amount and diversity of information available to design, implement, and support public services and policies.

Drawing from institutionalism, resource dependence theory, and collaboration scholarship, I developed a set of hypotheses that emphasize two dimensions of data access in local governments. First, a vertical dimension which includes institutions, the social environment - particularly power relationships - and coordination mechanisms implemented by managers. This dimension shows how exogenous - not controlled by public managers - and endogenous - controlled by public managers - factors contribute to a public organization’s ability to access resources. Second, a horizontal dimension which considers the characteristics of the actors involved in data exchange and emphasizes the institutional and social context of intra-organizational, intra-sectoral and cross-sectoral data access.

Hypotheses are tested using survey data from a 2016 nationally representative sample of 500 US cities with populations between 25,000 and 250,000. By focusing on small- and medium-sized cities, I contribute to a literature that typically focuses on data sharing in US large cities and federal agencies. Results show that the influence of government agencies and the influence of civil society have opposite effect on data access, whereas government influence limits data access while influence from civil society increases capacity to access data. The effectiveness of coordination mechanisms varies according to the stakeholder type. Public managers rely on informal networks to exchange data with other departments in the city and other governmental agencies while they leverage lateral coordination mechanisms - informal but unplanned - to coordinate data access from nongovernmental organizations. I conclude by discussing the implications for practice and future research.

In a contemporary socioeconomic context that pushes universities toward a more neoliberal agenda, some are answering a call to reinvest in the public purpose of higher education. Their strategies increasingly integrate teaching, research, and service through university-community partnerships. Within this movement, several initiatives aim to support a qualitative transformational shift toward a more egalitarian paradigm of collaboration. However, the literature and knowledge-building around these aims is largely insular to higher education and may be insufficient for the task. Thus, this study situates these aspirations in the community development literature and theories of power to better conceptualize and operationalize what is meant by reciprocal, mutually-beneficial approaches to university-community partnerships.

First, a theoretically grounded analytical framework was developed using both higher education and community development literatures to build two ideal-typical approaches to community practice characterized by power-over versus power-with. Within power-over, the institution exclusively holds authority, control, and legitimacy. Power-with is built through partnerships that share these elements with communities. Second, the resulting theoretical framework was developed further through a multi-stage deductive-inductive content analysis of written data readily available from university websites about their community partnerships. This process operationalized the framework by identifying and clarifying specific indicators within the power-over and power-with ideal-types.

The analytical framework was then compared to the aspirational community empowerment goals found in materials about the Carnegie elective classification for Community Engagement and materials from both the Anchor Initiatives Task Force and Anchor Initiatives Dashboard Learning Cohort. This comparative analysis found that while these initiatives aspire to transform power dynamics between universities and communities, they are vague on the meaning of these practices and their antitheses. This gap in clarity hinders these initiatives from distinguishing transformative work from the status quo, potentially inadvertently allowing the perpetuation of power-over dynamics in university-community partnerships.

The more robust analytical framework developed herein will enable these initiatives to better assess the quality of university-community partnerships against the aspirations of equity, social justice, democratic practice, mutual respect, shared authority, and co-creation. Such assessment will enable more effective knowledge-building toward transformational practice.

This dissertation examines gender differences in career advancement outcomes among academic science, technology, engineering and mathematics (STEM) scientists. In particular, this research examines effects of gender, PhD advisors and postdoctoral supervisors mentoring resources and gender homophily in the mentoring dyads on the career advancement outcomes at early career stages.

Female academic scientists have disadvantages in the career progress in the academic STEM. They tend to fall behind throughout their career paths and to leave the field compared to their male colleagues. Researchers have found that gender differences in the career advancement are shaped by gender-biased evaluations derived from gender stereotypes. Other studies demonstrate the positive impacts of mentoring and gender homophily in the mentoring dyads. To add greater insights to the current findings of female academic scientists’ career disadvantages, this dissertation investigates comprehensive effects of gender, mentoring, and gender homophily in the mentoring dyads on female scientists’ career advancement outcomes in academic science.

Based on the Status Characteristics Theory, the concept of mentoring, Social Capital Theory, and Ingroup Bias Theory, causal path models are developed to test direct and indirect effects of gender, mentoring resources, and gender homophily on STEM faculty’s career advancement. The research models were tested using structural equation modeling (SEM) with data collected from a national survey, funded by the National Science Foundation, completed in 2011 by tenured and tenure-track academic STEM faculty from higher education institutions in the United States. Findings suggest that there is no gender difference in career advancement controlling for mentoring resources and gender homophily in the mentoring dyads and other factors including research productivity and domestic caregiving responsibilities. Findings also show that the positive relationship between gender homophily in mentoring dyads and the reception of the mentoring resources, especially regarding providing help on career development and research collaboration, lead to enhanced early stage career advancement. Insights from the findings contribute both to theoretical understandings of the overall effects of gender, mentoring, and gender homophily in the mentoring dyads on female academic scientists’ career advancement at early career stages and to provide evidence of positive effects of same-gender mentoring dyads to universities.