Newer communication technologies (CTs) will always vie with more mature technologies for the attention of time-constrained legislators. As continual advances in CT make new methods of communication available to legislators, it is important to understand how newly introduced CTs influence novel and changing legislator behaviors. The mixed-method research presented in this study provides deep insights into the relationships between legislators and the CTs they use. This study offers many contributions, among them: it effectively bridges a gap between existing Internet Enabled CT (IECT) behavioral studies on non-legislators by expanding them to include legislator behavior; it expands existing narrowly focused research into the use of CT by legislators by including both IECT and mature CTs such as face-to-face meetings and telephone; it provides a fresh perspective on the factors that make CTs important to legislators, and it uncovers legislator behaviors that are both useful, and potentially harmful, to the process of democracy in the United States. In addition, this study confirms and extends existing research in areas such as minority party constituent communication frequency, and extends the topic of legislator CT behavior into some unanticipated areas such as constituent selective behaviors and the use of text messaging during floor debates which effectively enable lobbyists and paid consultants to participate real-time in floor debates in the Arizona House and Senate.
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.
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.
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.