Social and Behavioral Sciences Commons^™

Intersecting Identities And Adjustment To The Primary-Secondary School Transition: An Integrative Review, Joanne Harris, Rebecca Nowland, Megan Todd

Journal of Educational Research and Practice

The primary-to-secondary school transition is a milestone for children because of the multiple changes they must navigate. Although most adjust successfully, approximately 30% of children have difficulties during this transition. Intersecting identities are also likely to influence how children navigate the adjustment of the school transfer, but there have been no syntheses of existing evidence relating to the impacts of intersectionality. We conducted an integrative review using eight databases (Education database, ERIC, ProQuest Education, PsychInfo, Scopus, SocIndex, Sociology Database, and Web of Science) and searched for quantitative or qualitative studies that examined how intersecting identities impact children’s self-concept, mental health, …

Factors Associated With Gaps In Naloxone Knowledge: Evidence From A 2022 Great Plains Survey, Spencer Cooper‑Ohm, Patrick Habecker, Ryan Humeniuk, Rick A. Bevins

Department of Sociology: Faculty Publications

Background The rising prevalence of fast-acting opioids in the USA suggests the increased need for non-professional first responder administration of naloxone. Effective administration of naloxone during an overdose requires that bystanders are familiar with, have access to, and know how to use naloxone.

Methods Drawing on a statewide, address-based sample of Nebraskan adults, we used logistic regression to predict the likelihood of respondents’ familiarity with, access to, and competency to administer naloxone. Our independent variables included measures indicating proximity to drug use, perceived community stigma toward people who use drugs, and demographic data.

Results There were significant gaps in naloxone …

Bidder-Optimal Information Structures In Auctions, Dirk Bergemann, Tibor Heumann, Stephen Morris

Cowles Foundation Discussion Papers

We characterize the bidders' surplus maximizing information structure in an optimal auction for a single unit good and related extensions to multi-unit and multi-good problems. The bidders seek to find a balance between participation (and the avoidance of exclusion) and efficiency. The information structure that maximizes the bidders' surplus is given by a generalized Pareto distribution at the center of demand distribution, and displays complete information disclosure at either end of the Pareto distribution.

Spontaneous Self-Affirmation And Social Context As Moderators Between Stereotype Threat And Online Academic Performance, Katrina Hilton

Walden Dissertations and Doctoral Studies

Despite years of progress, there remains an academic achievement gap among minority and non-minority students in all levels of education. A possible reason for the persistent achievement gap is stereotype threat, which is a situational predicament that prompts individuals to perform in ways that mirror the stereotypes associated with their social groups. Self-affirmation interventions are often used to disrupt the effects of stereotype threat, as students are taught how to focus on their strengths and values to help improve their self-concepts. However, spontaneous self-affirmation techniques may be more impactful because students are able to automatically self-affirm in any psychologically threatening …

Thematic Analysis Through Artificial Intelligence (Ai), Prokopis A. Christou Phd

The Qualitative Report

Thematic analysis, a well-enforced qualitative analytic method, is likely to continue evolving with the adoption of AI technologies. This how-to report does not delve into the details of thematic analysis itself, as there are ample existing studies on the topic. Instead, it acknowledges the potential impacts, dynamics, and pitfalls of AI in thematic analysis while offering valuable advice, particularly for novice analysts, on how to incorporate and document AI tools in each phase of a thematic analysis. The author underscores the importance of not allowing AI to overshadow the analyst's critical evaluative and interpretive skills but instead supporting the use …

Centennial Library Shelf Life, January/February 2024, Cedarville University

Centennial Library Shelf Life

Articles in this issue: Biblical Heritage Gallery Exhibit: "You Live Where?", Students Enjoy Library Event, Library Career Opportunities, Library Careers Program: Notes from Our Interns, Digital Commons Publishing Corner, Library Showcases Student Art Work, Spotlight on Faculty Publishing.

Calming The Body, Calming The Mind: A Pilot Study On The Use Of Zero Balancing To Reduce Anxiety, Misty L. Rhoads, Mary Murphy

Journal of Transformative Touch

Background: The predominance of anxiety is currently at record levels, and the need for non-pharmaceutical approaches to help alleviate and decrease the harmful effects of anxiety on an individual and collective level is necessary. This study explored how Zero Balancing supports individuals with anxiety to manage their physical, mental, and emotional health more effectively. Researchers hypothesized that Zero Balancing would lower the perceived severity of general anxiety and lower perceived anxiety symptoms.

Methods: To honor the holistic nature of bodywork and the participants' lived experiences, the researchers utilized a concurrent mixed-methods phenomenological research design. Each participant received one Zero Balancing …

Pedagogy & The Ir: Using Gonzaga’S Institutional Repository For Teaching Resources, Elizabeth Wawrzyniak

Foley Library Scholarship

Teaching resources are a key element of educational success, both for educators and learners. Gonzaga University's Institutional Repository offers an expansive platform for hosting and accessing teaching materials, including syllabi, lecture notes, and other educational resources. By freely sharing these materials, faculty members not only enrich their own teaching practices but also contribute to the wider academic community. Join the Foley librarians to discuss how this repository can support your teaching, promoting actions that make scholarly and educational materials more accessible to all.

"They Are Usually Borderline Homeless": Exploring The Nexus Of Homelessness, Housing Instability, Successful Reentry, And Long-Term Reintegration, Emily Troshynski, Carolyn Willis

Criminal Justice Faculty Research

For previously incarcerated persons, affordable and safe housing options are scarce. Barriers to securing housing include federal mandates (i.e., eligibility requirements) as well as local rules and regulations (i.e., zoning and ordinances). When housing is available, disclosing criminal history on applications impacts individuals’ chances to rent (Philips & Spencer, 2013). A lack of a consistent rental history, no personal and/or employment references, and securing capital to cover security deposits are added challenges. Since parole rules direct ex-convicts not to associate with others that have a criminal record, living with partners, friends, and family members may not be an option. Research …

Intellectual Property Rights And Copyright Laws In The Regime Of Artificial Intelligence (Ai) In India, Hemavathy C

Library Philosophy and Practice (e-journal)

Artificial Intelligence (AI) has been developing for two decades. The application of AI is budding quickly in business dealings, corporate communication and legal services. AI and Law Forms are increasingly important in the legal arena as they play a significant role in the economy and society. Scientists and policymakers together are facing some of the hardest problems with the advancement of machine learning, cryptology and data protection. This paper is very helpful for policymakers, economists, lawyers and technocrats in the aspect of the ethical use of AI in data protection, privacy, security and social corners turns into very relevant issues …

Most Psychological Researchers Assume Their Samples Are Ergodic: Evidence From A Year Of Articles In Three Major Journals, Craig P. Speelman, Laura Parker, Benjamin J. Rapley, Marek Mcgann

Research outputs 2022 to 2026

Conventional statistics methods in most psychological research, such as null-hypothesis significance tests (NHSTs), use aggregated values (i.e., the sample means) of group behaviours to make inferences about individuals. Such inferences are possibly erroneous because groups of humans rarely, if ever, constitute an ergodic system. To assume ergodicity without checking is to commit the ‘ergodic fallacy’. The aim of the current study was to examine the prevalence of this error in contemporary psychological research. We analysed three highly cited ‘Q1’ journals in the fields of clinical, educational and cognitive psychology for statements that indicated this error. As hypothesized, the ergodic fallacy …

Análisis Sociolingüístico De Una Hispanohablante En Harrisonburg, Virginia/Sociolinguistic Analysis Of A Spanish Speaker In Harrisonburg, Virginia, Tessa Adams

James Madison Undergraduate Research Journal (JMURJ)

Los patrones dialectales de hispanohablantes nativos quienes saben inglés como un idioma segundo han sido un foco para académicos lingüísticos por mucho tiempo. El estudio presente compara las experiencias de una hispanohablante nativo biligüe de Harrisonburg, Virginia, con patrones de voz que son común en otras investigaciones más amplias. Utilizando un formato de entrevista estructurado y un análisis hecho como en un caso práctico, la escritora muestra que que los rasgos lingüísticos de “Mirabel” alinea con aspetos claves de escolaridad existente mientras probando como una excepción a otras tendencias establecidas.

The dialectical patterns of native Spanish speakers who know English …

Impact Of Equine Interaction During Psychotherapy On Anxiety And Depression For Residential Treatment Program Patients Experiencing Substance Withdrawal, Molly M. Friend, Molly C. Nicodemus, Clay Cavinder, Caleb Lemley, Pauline Prince, Katherine A. Cagle-Holtcamp, Rebecca M. Swanson

People and Animals: The International Journal of Research and Practice

As incidences of substance use disorders (SUD) increase in the wake of the COVID-19 pandemic, there is a need for more effective treatment approaches. Further, treatment approaches currently available struggle to retain patients during the period of substance withdrawal in early treatment due to patients’ withdrawal symptoms including increased feelings of anxiety and depression. Withdrawal symptoms have been linked to dysregulated cortisol concentrations present in this period. Psychotherapy incorporating equine interaction (PIE) has emerged in other populations as a treatment that decreases cortisol concentrations and improves treatment retention. The present study investigated the impact of 4 weeks of PIE on …

“Here, Kitty, Kitty.” Community Perceptions Of Free-Roaming Cats: A Northern Canadian Case Study, Annie Booth, Ken Otter

People and Animals: The International Journal of Research and Practice

Free-roaming domestic cats (Felis catus) create controversy, due to their tendency to invade neighbors’ gardens, hunt wildlife, and create disturbances. Municipal governments are often under pressure to address concerns regarding free-roaming cats. As approximately 28% of the 8.8 million cats owned in Canada free-roam (are allowed outside unsupervised and unconstrained), understanding owner rationales for letting the cat out is important for officials tasked with addressing public concerns. In 2019, we studied attitudes toward cats within a north-central British Columbia, Canada, city. The rationales cat owners use to justify free-roaming, as well as their perceptions about the risks and …

Toward Energy-Efficient Deep Neural Networks For Forest Fire Detection In An Image, Yali Wang, Chuulabat Purev, Hunter Barndt, Henry Toal, Jason Kim, Luke Underwood, Luis Avalo, Arghya Kusum Das

The Geographical Bulletin

Forest fires cause huge losses and are a serious problem facing many countries worldwide, including the USA, Canada, Brazil, Siberia, and Indonesia, to name a few. Automatic identification of forest fires in an image is thus an important field to research in order to minimize disasters while also helping in mitigation planning and designing rescue tactics. Artificial Intelligence technologies, especially deep neural networks, have emerged recently with promises to detect fires with better accuracy from an image. However, the massive energy consumption of deep neural networks thwarts their widespread adoption, especially when it comes to onsite detection of fire utilizing …

Gis-Based Spatial And Temporal Analyses Of Motor Vehicle Crashes In The Atlanta Metropolitan Region 2017-2021, Heyward Stober, Jeong C. Seong

The Geographical Bulletin

Motor vehicle crash analysis is among the most insightful metrics for public safety officials, researchers, and drivers. In this article, geographical information systems (GIS) tools were used to study the spatial and temporal trends of traffic crashes and fatal crashes. The methodology involves collecting spatial crash data over time and using computer-based analysis to overlay the road data against various spatial and temporal parameters in the Atlanta metropolitan region. Results show major crash hotspots in the region, such as the cites of Marietta, Kennesaw, and College Park. Hotspots tend to form on interstate highways, while smaller state highways have fewer …

Recovery Of Microtopography Following Prairie Restoration: Implications For Biodiversity Monitoring, Karli Cich, Scott Powell

The Geographical Bulletin

Tallgrass prairies are often restored from agricultural fields where the natural microtopography has long since been removed. Therefore, our study investigates the degree to which restored prairies recover microtopography. Differences in microtopography were measured using precise elevation data collected from LiDAR to compare differences in microtopography between crop fields, fallow fields, newer restored prairies, and older restored prairies. We also compared plant biodiversity indices between newer and older restored prairies using nested plot vegetation sampling. Our first research question is how microtopography differs between the sites. Our results show that older restored prairies had the most microtopographic variation, followed by …

Modeling The Impact Of Ocean Temperature Increases On The Distribution Of Seagrasses Around The Korean Peninsula Using A Machine Learning Technique, Jina Jang, Seohyeon Kim, Jeong Seong

The Geographical Bulletin

Seagrasses are important resources which form a vital part of the ocean ecosystem. They are also considered blue carbon because of their capability of sequestrating carbon. Seagrass distribution can be affected by many factors including ocean temperature. It is highly likely that recent climate change may increase ocean temperature significantly in East Asia and consequently alter seagrass distribution patterns. This study aims at predicting the impact of ocean temperature increases on seagrass habitats around the Korean Peninsula. Using the Maximum Entropy (MaxEnt) Model, seagrass habitat distributions were modeled when sea temperature rises by 1°C, 2°C, 3°C, and 4°C. Results show …

Predicting Cloud Fraction With Instantaneous Direct And Diffuse Shortwave Solar Irradiance, Jamison Lerma, Emily K. Blackaby, Maosi Chen, Sasha Madronich, Wei Gao

The Geographical Bulletin

The purpose of this study is to compare the different performances of three commonly used models (i.e., linear regression, random forest regression, and deep neural network (DNN)) to predict cloud fraction (CF) using ground-based shortwave solar radiation measurements and analyze the importance of the input features. The CF data are obtained from the Surface Radiation Budget (SURFRAD) and the Atmospheric Radiation Measurement (ARM) and the irradiance data from the USDA UV-B Monitoring and Research Program. The study finds that CF of opaque and total clouds can be best predicted using both Random Forest Regression and DNN with the validation R2 …

Prediction Of Traffic Congestion Using A Time-Series Model And Spatiotemporal Data: A Case Study Of The Atlanta Downtown Connector, Yunsik Kim

The Geographical Bulletin

Traffic congestion poses significant socio-economic challenges, and many urban commuters experience time and cost burdens due to traffic jams. Effectively managing and predicting traffic congestion is crucial for contemporary urban planning and operations. This study aims to predict congestion using time-series deep learning models, focusing on a chronically congested road section. The research area is the Atlanta Downtown Connector, a heavily trafficked route passing through the heart of the city of Atlanta. To address issues often associated with sensor and GPS-based data collection, traffic data was obtained from an open-source online map service, Google Maps. A multivariate time-lagged LSTM model …

A Remote Sensing Investigation Of The 2022 Invasion Of Eastern Ukraine On Agricultural Landcover, Michael S. Agbozo, Luke J. Marzen, Chandana Mitra

The Geographical Bulletin

Ukraine-Russian political relations over the years have alternatively experienced periods of tranquility and turmoil with violent conflicts since 1917, including the events of the 2014 annexation of Crimea and the 2022 Russian invasion of the entirety of Ukraine. These conflicts remain developmental threats and their assessment requires multi-perspective analysis. Understanding the spatial dimensions of such conflicts and their consequences on physical and social spaces at varying scales could provide credible scientific impetuses on which targeted post-conflict remediations could be built. This preliminary study therefore takes advantage of the capabilities of satellite remote sensing, to provide quick and effective spatiotemporal analysis …

Open-Source Based Change Pattern Analysis Of Urban Green Spaces Using Landscape Metrics, Mohammad Anwar Alattar

The Geographical Bulletin

A growing number of studies have been conducted on urban green spaces (UGSs), given their essential role in mitigating urbanization externalities. The current available methods for acquiring and analyzing UGSs data suffer from several limitations. For example, free satellite imagery exhibits pixel distortion and fails to account for fine-grained structure such as accurate geometry or size. Moreover, official UGSs datasets are typically updated periodically, not continuously. This work provides a Python-derived open-source based analysis for acquiring, modeling and analyzing UGSs change patterns using landscape metrics. To demonstrate the feasibility of the proposed approach, it is applied on the New York …

High-Mountain Hazards In The Indian Himalaya: An Assessment Of The Causes And Effects Of The Chamoli Flood In 2021, Christina M. Salzmann, Sarah J. Halvorson, Anna E. Klene

The Geographical Bulletin

On 7 February 2021, a devastating flood severely impacted the Ronti Gad, Rishiganga, and Dhauliganga River Valleys in the northwestern District of Chamoli, India. The flood washed away two hydropower projects and caused more than 200 fatalities. This study assessed some of the causes and effects of this catastrophic flood event and aims to provide further documentation that the event was not caused by a glacial lake outburst flood, as many reports initially indicated. Analysis of high-resolution satellite imagery, digital elevation model (DEM) differencing, and precipitation and temperature data showed that an ice-rock avalanche was released as a result of …

Evaluating The Use Of Unpiloted Aerial Systems To Detect And Monitor Beech Bark Disease In New England Forests, Isabelle Lopez, Benjamin T. Fraser, Russell G. Congalton

The Geographical Bulletin

The American beech (Fagus grandifolia) plays a key role throughout eastern North American forests. However, beech bark disease (BBD) causes widespread mortality of beech trees. We investigated whether imagery collected using an unpiloted aerial system (UAS) could differentiate beech tree health. Reference data were collected from 140 beech trees in New Hampshire and were visually classified as having “no/trace damage,” “moderate damage,” or “heavy damage.” Multispectral imagery was collected from a UAS, and 44 image features were derived for each beech crown. We used machine learning to identify the importance of each feature in distinguishing between the three health classes …

Editors' Note, Jc Seong

The Geographical Bulletin

Editors' Note

Volume 64-2 Complete Issue, Nancy Pullen-Hoalst

The Geographical Bulletin

Complete Issue

Front Matters, Nancy Pullen-Hoalst

The Geographical Bulletin

Front Matter

Religion And Gender-Based Preferences In Therapist Selection Among Orthodox Jews, Yehuda L. Rosen

Walden Dissertations and Doctoral Studies

The preferences of Orthodox Jews when choosing a therapist are important to understand, as they can inform practice for individuals, clinics, and referral agencies. The purpose of this study was to determine the preferences for gender-matched therapists, Orthodox Jewish therapists, and specific therapist characteristics among Orthodox Jews. The study was based on Bordin’s working alliance model of psychotherapy, which contends that a strong working alliance is necessary for effective psychotherapy. The research questions were used to explore whether Orthodox Jewish men and women differed in their preferences for gender-matched or Orthodox Jewish therapists, whether religiosity predicted a preference for gender-matched …

Clean Investment Monitor: Q4 2022 — Q3 2023, Madison Dwyer, Zachary Billot, Annie Vong, Caitlin J. Saladino, William E. Brown Jr.

Environment

This fact sheet presents investment trends in clean manufacturing, energy and industry, and retail in the Mountain West states of Arizona, Colorado, Nevada, New Mexico, and Utah. This fact sheet examines data from the Q3 2023 update of the Clean Investment Monitor (CIM), a joint project of Rhodium Group and the MIT Center for Energy and Environmental Policy Research.

The Cowl - V. 88 N. 3 - February 8, 2024

The Cowl

The Cowl - student newspaper of Providence College. Vol. 88 No. 3 - February 8, 2024. 24 pages.