|Friday, March 4th|
9:00 AM - 9:15 AM
Social scientists often utilize either qualitative or quantitative methodology to study the human experience through gathering information or data on human behavior. This leads to insights into how we view individuals, learn about relationships, ways people make decisions, and relationships between beliefs and behaviors. One overlooked and underused dynamic methodology is the Q method. Q methodology offers a combination of qualitative and quantitative methods that accurately provides a unique way of gathering, sorting, and studying the values and beliefs of participant (Watts, & Stenner, 2005). The following presentation overviews the purpose, history, and practical application of the Q methodology. Examples will be explored, and participants will have an opportunity to experiment with Q method research design, to allow for better understanding of method and how it can be applied to various fields.
Limited research suggests the use of Q methodology appears less used than the more common qualitative or quantitative methodologies (Newman & Ramlo, 2010). Q methodology is designed for multiple disciplines seeking to research the held beliefs and values of participants about a particular phenomenon. This approach provides rich descriptions of different points of view that exist around a topic, often leading to finding of new perspectives and insights while using quantitative analysis. The method captures individual connections to the statements. In essence, Q methodology is a study of human subjectivity (McKeowan & Thomas, 1988).
Q methodology was designed by William Stephenson (1935) as a specific new method at the time to study the values and beliefs of research participants. While it is not a particularly new method, its uniqueness and ease of use deserves increased attention and knowledge. McKeowan & Thomas (1988) address the importance of Q methodology as a method in which ‘the respondents frame of reference’ is preserved suggesting that Q methodology is aimed for multiple disciplines that are seeing to increase rigor in the study of human subjectivity. According to Richardson, Fister, & Ramlo, (2014), a primary difference in the Q method is a process called Q sort. Q sorting, which appears as an upside-down bell curve with a scale of ‘agree to disagree’ allows the participant to be actively engaged in the communication of their view. Watts & Stenner (2005), illuminate the importance of enabling the researcher to see the ways’ themes are interconnected, rather than breaking them apart preserving participants views.
The Q approach uses participants beliefs and values about certain subjects to inform new practices. For example, a study done by Richardson, Fister, & Ramlo (2014) provided a pre-test Q sort to college-age students pursuing an exercise science degree. Q methodology was chosen due to being ideal for researching the range and diversity of subjective experiences, perspectives, and beliefs. Results revealed that students maintained some bias about working with those struggling with obesity. A specific workshop was created into the curriculum addressing potential biases and gaps in knowledge and followed up with Q sort to measure changes in beliefs and values. The uniqueness of Q methodology allows researchers to capture narrative content to create appropriate interventions. Participants of this presentation will engage in a hands-on demonstration, easing the understanding and application of a Q sort. The presentation will also include a brief overview of the factor analysis to increase understanding of use of this methodology across various disciplines.
Barker, S.L., Maguire, N., Bishop, F.L & Luisa, L. (2018). Expert Viewpoints of PeerSupport for People Experiencing Homelessness: A Q Sort Study. American Psychological Association. 16 (3): 402–414 1541-1559. http://dx.doi.org/10.1037/ser0000258
McKeown, B. & Thomas, D. (1988). Q Methodology. Sage Publishing
Newman I, Ramlo S. (2010). Using Q methodology and Q factor analysis in mixed method research. In: Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.), edited by Tashakkori A, Teddlie C. Thousand Oaks, CA: SAGE, p. 505–530.
Richardson, L.A., Fister, C.L, Ramlo, S.E (2014). Effect of an exercise and weight control curriculum; views of obesity among exercise science students. Journal of Advanced Physiological Education. (39): 43-48.
Watts, S. & Stenner, P. (2005). Doing Q methodology: theory, method and interpretation. Qualitative Research in Psychology, (2), 67-91.
9:20 AM - 9:35 AM
In Graph Theory we describe an object called a graph G(V,E) which is a set of vertices, V, and the set of edges, E, between the vertices. Practically any type of system which can be described by a network, such as the interaction between neurons in the brain, the connections within a crime ring, or species migration between islands in the South Pacific, can be modeled at some level by a graph. Within theoretical mathematics they provide an enormous field of study in combinatorics with applications in geometry, number theory, and probability.
One graph model we explore in our research is that of a randomly perturbed graph. This model begins with an arbitrarily dense graph with minimum degree d, where degree is the number of edges incident to each vertex. To this graph we add m additional edges to get our final graph G. We then randomly color edges with r colors. Based on a conjecture by Anastos and Frieze from 2019, we have shown that with r=5 and m constant, G is rainbow connected with high probability. A graph is connected if there is an edge path between any two vertices. A graph is rainbow connected if there exists a path between any two vertices where no color is repeated along the path.
We relied heavily on the probabilistic method to prove our statement. The probabilistic method lies at the junction of discrete math and probability theory. The method involves proving the existence of a structure with desired properties by defining an appropriate sample space of structures and showing that the a structure with desired properties exists in the sample space with positive probability. Thinking of it conversely, the probability that the structure with the desired properties does not exist is less than one in violation of Kolmagrov's axioms.
This presentation will introduce the notions of Graph Theory required to understand our result. Additionally, it will be an introduction to the probabilistic method which is likely to be novel to people who are not specialized in the area, but has increasingly shown its far reaching applications. Finally, this presentation will show the use of the probabilistic method within our argument. My hope is that this will provide a general audience an understanding of our result and the method used to prove it without straying too far into the thicket of discipline-specific details.
Matthew J. Swarr, University of Montana, Missoula
11:00 AM - 11:15 AM
In the western US, water resources used for agricultural, domestic, and industrial purposes are largely derived from high-elevation watersheds. As a result of increasingly severe annual drought and growing population, the need for finer-scale estimates of terrestrial water storage (TWS) for individual watersheds has grown. Current hydrologic models commonly underestimate TWS, as topography, climate, lateral heterogeneity in geology, and subsurface changes in storage are difficult to incorporate in hydrologic models [Argus et al., 2017]. The Gravity Recovery and Climate Experiment Follow-on (GRACE-FO) TWS measurements offer accurate measurements at a continental scale (~300-400 km), but coarse spatiotemporal resolution and a one-month data latency make it unreliable as a tool for water management at a local scale [Fu et al., 2015]. Other recent advances in space geodesy, such as Global Navigation Satellite Systems (GNSS), allow for higher-resolution estimates of TWS to be made from observing deformation of Earth’s surface resulting from the redistribution of water. Changes in water mass on/beneath Earth’s surface produce vertical and horizontal elastic deformation of the Earth that is observable by GNSS antennas. Before estimates of TWS can be made for mountain watersheds (e.g., Hydrological Unit Code (HUC)-4 and smaller) using real geodetic observations, it is crucial to determine the spatiotemporal resolution in which TWS can be estimated for a given network of GNSS antennas. The spatial scale in which TWS can be derived is dependent upon the density and configuration of GNSS antennas within a region, a-priori hydrologic information, and inversion algorithm/parameters. Previous studies have been shown to estimate TWS at a regional scale [e.g., Borsa et al. 2014]; however, TWS estimates have yet to be made for individual mountain watersheds. With new advances in approach, such as incorporating a priori information from existing hydrology models and strategic deployment of GNSS antennas, spatiotemporal resolution of TWS estimates is likely fine enough for estimates to be made for individual watersheds. Using LoadDef [Martens et al., 2019], a modeling software used to model elastic deformation of the Earth, a series of synthetic loads will be forward modeled and inverted for the pre-existing Selway-Lochsa GNSS network located in the Bitterroot and Sapphire Mountains along the Montana-Idaho border, the first GNSS network specifically designed to observe changes in TWS at a watershed-scale. Synthetic loads will take the form of checkerboards, containing square loaded and unloaded areas of varying scale, as well as real hydrologic datasets such as SNODAS snow water equivalent (SWE) estimates and NLDAS Soil Moisture estimates to determine how effectively the existing network configuration can return a given synthetic load with varying spatial resolution and distribution. Additionally, a synthetic GNSS network can be designed and rearranged, including additional synthetic GNSS stations, using LoadDef to determine the optimal network configuration for estimating TWS at a watershed-scale and to determine the impact of adding additional stations to the existing network. Placing quantitative limits on model resolution advances understanding of TWS distribution and uncertainties as well as optimal GNSS network design. By improving the ability to accurately estimate TWS in mountain watersheds, we improve the ability to monitor and manage freshwater resources in the context of a changing climate.
Rebekah Brassfield, University of Montana, Missoula
11:20 AM - 11:35 AM
Geographic distribution of plants and animals is determined by a variety of overlapping habitat factors like soil type, elevation, or canopy cover. Understanding the complicated interactions between these factors and the impacts they have on species’ distributions is increasingly important in the face of changing environments and climates. Species distribution models (SDM) measure the importance of habitat variables in determining the spatial distribution of certain species. Because SDMs include a variety of habitat variables, they can be used to answer questions about habitat suitability, predict future distributions, and inform conservation efforts.
Huckleberries (Vaccinium spp.) are a common understory shrub in the Western United States. They are culturally important to the indigenous people in the area as well as being ecologically important as a keystone species. Like all plants, huckleberries have a limited range of conditions they typically grow in, and as their habitat and abundance declines, understanding the factors that impact their distribution is vital to their conservation. Using locations across western Montana, an SDM was fit by collecting 13 biotic and abiotic habitat variables. The results of the model indicate that the most important variables for huckleberry presence were canopy cover, elevation, and precipitation.
A useful application of SDMs is predicting species distributions based on future climate scenarios. With massive shifts in climatic variables expected in the near future, habitat ranges will begin to shift to areas that meet the requirements they have for successful growth. Using the results of the original SDM, a new model was fit using climate projections for annual temperature and precipitation to determine what areas will meet the habitat requirements of huckleberries in the future. SDMs provide land managers and scientists with species distributions that can be used to inform management decisions and target critical habitats. Finally, by incorporating future climate scenarios into predictions, we can understand how organisms might respond to climate change and be better prepared for an uncertain future.
Emory C. Padgett, University of Montana
1:30 PM - 1:45 PM
From Norman Maclean’s A River Runs Through It (1976) to the popular series Yellowstone, stories loom large in Montana, and their use goes beyond entertainment. Stories about the state are informative in understanding Montana culture and heritage because the myths, perspectives, and truths revealed through literature, art, and television are closely intertwined with the memories and values of its people; in an ongoing feedback, stories simultaneously originate in lived experience and actively shape experiences. Grounded in this cultural significance, I use media as an ethnographic lens through which to study social change in rural Montana, which has faced economic uncertainty, undergone volatile population shifts, and struggled with mental health crises. This approach, coupled with ethnographic vignettes as a historic preservation intern and interviews of Montana writers and heritage professionals, serves as the foundation for my thesis on rural Montana. Ultimately, this understanding will contribute to better understanding of why Montana experiences such high suicide rates. Suicide is a complex biopsychosocial phenomenon that requires close cultural study to properly prevent.
I first encountered Montana literature as an AmeriCorps; Kittredge and Smith’s (1990) anthology, The Last Best Place, seemed near-ubiquitous as out-of-staters sought to understand the new communities they were serving in. At the yearly conference, Red Ants Pants founder Sarah Calhoun cited Doig’s 1978 This House of Sky as the reason for her moving to Montana. These stories—and their prominence—lingered in my mind, and when I read ethnographies as a graduate student that wove literature into arguments, I knew that the richness and depth of work produced by Montana writers would be—appropriate for Montana—a gold mine. So, in this paper, I draw upon Montana novelists (fiction and non-fiction) and poets in all their geographic, ethnic, and gender diversity to produce a portrait of rural life and values; I compare this literature to broader media like lifestyle magazines and the show Yellowstone to illustrate the varied and often contradictory claims about authenticity and realities of life in Montana. To deepen understanding, I interviewed prominent writers and heritage professionals around the state about their views on rural life, cultural conflicts, and the future of heritage in Montana. Finally, this mosaic of sources is supplemented by personal experience performing historic restoration in rural areas around Helena and my interactions with people who were concerned about legacy and the representation of their stories in the built environment.
Though Montana media receives much attention, Montana, especially rural Montana, is often forgotten by researchers. My thesis constitutes one of the first anthropological studies of the state, and my attempt to define a rural Montana heritage is novel—as is my combination of methods, which is interdisciplinary and combines ethnography and literary analysis.
Ultimately, this paper will serve as the foundation of my thesis, which asks if heritage and social change might impact the wellbeing of communities and individuals within them. So, in addition to providing Montana anthropologists with a baseline of understanding of prominent cultural traits of the state and thus inform future research, it is hoped that my research will contribute to public health’s efforts to treat mental health crises throughout rural Montana.
Jerod G. Peitsmeyer, University of Montana, Missoula
1:50 PM - 2:05 PM
Physical experiences with ancient art objects in museums are rare. Display paradigms in most public institutions continue to propagate systems of participant interaction that reinforces unequal power structures.
The Montana Musuem of Art and Culture (MMAC) is the current custodian of an ancient, Rhodian wine amphora that provides an opportunity to examine a novel system of somatic participation. This proposal upends traditional gatekeeping practices and serves as a powerful and progressive, humanist touchstone; an olive branch extended to the general public from behind the walls of higher education and the ramparts of privileged scholarship. This study reimagines the amphora's future custody and suggests a purely somatic method of display that dispenses with traditional, institutional supplementation. The MMAC’s potential somatic exhibition encourages touching the surface of a 2300-year-old artifact. This experiment offers museum goers a novel chance to create autonomous knowledge through touch while simultaneously bridging chasms in educational backgrounds and cultural privileges.
This proposal draws on defensible and pertinent philosophical and theoretical positions to argue for a method of museum practice that will transform and decolonize audiences’ interactions with classical objects from a prescribed and narrow interplay into a more equitable and democratic interrelation. I illuminate a need for the objects that chronicle a segment of our shared history (classical objects in particular) to be made available to museum visitors for direct, physical touch.