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MSW Portfolio
No full textComprehensive Collection of work that reflects my academic, professional, and personal growth throughout the Master of Social Work Program. It highlights my development across core Social Work competencies, advocacy, family reservation, and trauma-informed care in Indigenous communities. Each section showcases key assignments, reflections, and professional experiences demonstrating my ability.https://scholarworks.umt.edu/grad_portfolios/1437/thumbnail.jp
Master of Social Work Portfolio
Get PDFhttps://scholarworks.umt.edu/grad_portfolios/1454/thumbnail.jp
Cultivating My Social Work Identity: Integrating Past, Context, and Relationship
Get PDFMy application to the Master of Social Work (MSW) program was sent as a means to move beyond the constraints of the classroom walls as teacher and provide meaningful and tailored support to individuals who were falling through the cracks of the system. My experience in this program was transformative, in ways that were expected and unexpected. I recognize significant expansion in my perspective alongside growing confidence in applying newly acquired skills, both clear indicators of my professional and personal development. The insights garnered from personal experiences, academic lectures, and practicum placements shifted my theoretical foundations and personal worldviews. What I have learned could easily become a library, but for the sake of brevity, I will limit it to a glimpse of how I have begun to develop the knowledge, skills, values, and cognitive and affective awareness essential to thrive in my role as a social worker.https://scholarworks.umt.edu/grad_portfolios/1461/thumbnail.jp
2024 Estimates - Nonresident Visitation, Expenditures, and Economic Contribution
Get PDFThis report is a collection of estimates of 2024 nonresident visitation to Montana, expenditures by nonresident travelers in the state, and the contribution to Montana\u27s economy of that traveler spending. Included are estimates by full year, quarter, trip purpose, and other visitor segments
Bridging the gap between plot-level and landscape-scale analysis for wildfire risk assessment
No full textRemote sensing technology has advanced greatly over the past couple of decades proving its ability to aid in wildfire risk assessment and improve our understanding of forest structure and fuel inventory across the landscape. While some aerial and satellite sensors perform better than others, they all have a common weakness, their reduced ability to capture understory fuels with high detail. Terrestrial laser scanning is an emerging solution due to its understory perspective. This research leverages the beneficial aspects of both terrestrial laser scanning and various aerial- or satellite-based remote sensing platforms (aerial laser scanning, digital aerial photogrammetry, and Sentinel-2) to capture highly detailed fuel loading and structure across large spatial extents. This study took place in dry-mixed conifer and moist-mixed conifer forests along the East Cascades in Washington State. A robust sample design was used to allow for extrapolation across large areas of the landscape. A multi-stage modeling approach linking field measurements to terrestrial laser scans and then to landscape scale sensors was used to predict common fuel inputs (duff bulk density, woody bulk density, non-woody bulk density, average canopy base height, and canopy bulk density) to fire behavior models. I compared the explanatory power of this approach to a more traditional approach that does not include terrestrial laser scanning. Predictions of woody bulk density and average canopy base height benefited most from the use of terrestrial laser scanning, reducing the root mean square error by 0.1354 and 0.3374, respectively. Duff bulk density, non-woody bulk density, and canopy bulk density showed minimal benefit or slightly reduced model performance with the addition of terrestrial laser scanning. This study demonstrates the potential to increase sampling efficiency with the use of terrestrial laser scanning to better capture fine-scale nuances in forest structure and fuel characterization
EVALUATING THE ACCURACY OF STATURE ESTIMATION FROM TIBIAL RADIOGRAPHS USING KNOWN AND NEWLY DEVELOPED REGRESSION FORMULAS
Get PDFThis study assesses the accuracy of stature estimation from tibial radiographs using digital measurements as an alternative to traditional osteometric tools. Stature estimation is crucial in forensic anthropology for identifying individuals, especially cases involving skeletal remains. Traditional methods rely on physical measurements and established regression formulas, such as those by Trotter & Gleser (1958).
This research analyzed tibial radiographs from the Forensic Anthropology Skeletal Trauma (FAST) database with ImageJ software to measure tibial lengths digitally. The sample included 59 tibiae, with measurements compared against three regression formulas; Trotter & Gleser (1958), Simon et al. (2023), and a new regression formula developed specifically for this dataset and method. Key metrics, such as correlation coefficients, mean and median errors, and standard error were used to evaluate each formula’s accuracy. Additionally, a One-way ANOVA was run to compare the means of the stature estimates produced by each formula. Tukey’s pairwise test was used to further investigate differences between individual formulas.
Results demonstrated that the new regression formula performed equally to both the Trotter & Gleser and Simon et al. formulas. The one-way ANOVA and Tukey’s pairwise test showed there was no significant difference between the three formulas. The results provide evidentiary support that the new formula emphasizes the potential of digital measurements as a reliable and alternative for stature estimation. These findings suggest that digital measurement techniques could enhance forensic anthropology by offering a practical, culturally sensitive approach to building biological profiles