Doctor of Philosophy

dissertationThe United States federal government funds two distinct types of school systems on or near indigenous lands: tribally controlled schools and Bureau of Indian Education (BIE)-operated schools. This study fills a void in the scholarly research on differences in teacher working conditions and job attitudes across all 170 of these two types of schools that are located in 23 states and on 64 Indian nations. This study utilized cross-sectional survey data from the 2007-2008 administration of the Schools and Staffing Survey (SASS), which was conducted by the National Center for Education Statistics (NCES) and the U. S. Census Bureau. This project was undertaken in order to determine the existence of differences in perceived teacher job attitudes and working conditions across four classifications of schools with high Native American Alaskan Native (NAAN) enrollments. The study analyzed the responses from 1290 teachers who were sampled from 540 schools across the BIE and public sectors. Analytical techniques incorporated included confirmatory factor analysis of measures of organizational commitment, administrative support, teacher autonomy and student engagement, and multiple regression and group means analyses. In addition to the BIE-operated and tribally controlled schools, also incorporated into the analysis are state-funded public schools with high Native American Alaskan Native enrollments. The results of this study have verified that administrative support is highly associated with each of the teacher job attitudes: organizational commitment, job satisfaction, and pay satisfaction. Teachers at tribally controlled schools report greater perceived job satisfaction than do their public school counterparts at schools with high Native American Alaskan Native enrollments, and tribally controlled school teachers report much less satisfaction with their pay than do their peers at Bureau of Indian Education schools. There are significant salary disparities between the Bureau of Indian Education-operated and tribally controlled schools on the four salary points examined, and teacher experience levels both at their current school and over their careers are significantly greater for Bureau of Indian Education teachers as compared to teachers at tribally controlled schools. Study findings possess significant potential to inform the tribal and federal policy-making processes with respect to the furtherance of tribal sovereignty in education and to optimize school resource allocation practices. At the state level, information from the study may be utilized in reforming principal preparation programs via the inclusion of teacher job attitude research

More Progress Toward a Taxonomy of Managerial Performance Requirements

The purpose of this study was to derive inductively a taxonomy of managerial performance requirements from many empirical studies of manager perfor- mance. Toward that end, 26 dimension sets were first gathered from published and unpublished studies of manager performance. Most of these studies in- volved critical incidents, and all of them were empirically based. lbenty-five industrial psychologists experienced in research on managers then indepen- dently sorted the 187 managerial performance dimensions into categories ac- cording to perceived similarity in content. These sortings were used to construct a pooled 187 times 187 correlation matrix, and the matrix was factor analyzed. The 18-factor solution is offered as an inductively derived, expert judgment-based summary of managerial performance requirements, using data from many manager jobs and numerous organizations. This taxonomy is compared to other dimension sets, and its potential usefulness discussed

The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource

The Neotoma Paleoecology Database is a community-curated data resource that supports interdisciplinary global change research by enabling broad-scale studies of taxon and community diversity, distributions, and dynamics during the large environmental changes of the past. By consolidating many kinds of data into a common repository, Neotoma lowers costs of paleodata management, makes paleoecological data openly available, and offers a high-quality, curated resource. Neotoma's distributed scientific governance model is flexible and scalable, with many open pathways for participation by new members, data contributors, stewards, and research communities. The Neotoma data model supports, or can be extended to support, any kind of paleoecological or paleoenvironmental data from sedimentary archives. Data additions to Neotoma are growing and now include >3.8 million observations, >17,000 datasets, and >9200 sites. Dataset types currently include fossil pollen, vertebrates, diatoms, ostracodes, macroinvertebrates, plant macrofossils, insects, testate amoebae, geochronological data, and the recently added organic biomarkers, stable isotopes, and specimen-level data. Multiple avenues exist to obtain Neotoma data, including the Explorer map-based interface, an application programming interface, the neotoma R package, and digital object identifiers. As the volume and variety of scientific data grow, community-curated data resources such as Neotoma have become foundational infrastructure for big data science

The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource

The Neotoma Paleoecology Database is a community-curated data resource that supports interdisciplinary global change research by enabling broad-scale studies of taxon and community diversity, distributions, and dynamics during the large environmental changes of the past. By consolidating many kinds of data into a common repository, Neotoma lowers costs of paleodata management, makes paleoecological data openly available, and offers a high-quality, curated resource. Neotoma's distributed scientific governance model is flexible and scalable, with many open pathways for participation by new members, data contributors, stewards, and research communities. The Neotoma data model supports, or can be extended to support, any kind of paleoecological or paleoenvironmental data from sedimentary archives. Data additions to Neotoma are growing and now include >3.8 million observations, >17,000 datasets, and >9200 sites. Dataset types currently include fossil pollen, vertebrates, diatoms, ostracodes, macroinvertebrates, plant macrofossils, insects, testate amoebae, geochronological data, and the recently added organic biomarkers, stable isotopes, and specimen-level data. Multiple avenues exist to obtain Neotoma data, including the Explorer map-based interface, an application programming interface, the neotoma R package, and digital object identifiers. As the volume and variety of scientific data grow, community-curated data resources such as Neotoma have become foundational infrastructure for big data science