Is What I Do Who I Am? A Study of Romantic and Sexual Partnering and Identity

Honors (Bachelor's)PsychologyWomen's StudiesUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/107758/1/manleymh.pd

Conceptual Understanding of Linear Relationships Across Various Mathematics Courses

This cross-sectional study investigated the conceptual understanding of linear relationships for 195 students enrolled in a single school in a large, urban district across five mathematics courses: Grade 7 Math (n = 24), Grade 8 Math (n = 52), Geometry (n = 43), Algebra 1 (n = 31), and Algebra 2 (n = 45). The following questions guided this study: (1) What differences exist in students’ conceptual understanding of linear relationships across mathematics courses? (2) What are common strengths and weaknesses in students’ conceptual understanding of linear relationships? An assessment was created to assess three constructs of conceptual understanding of linear relationships: (1) Identifying unit rates in proportional relationships, (2) Moving fluidly between representations of the same linear relationships, and (3) Interpreting different representations of linear relationships. The assessment contained eight multiple-choice items and seven free-response items, with five items assessing each construct. Each student completed the assessment in their regular mathematics course in a single class period. The assessment was scored and analyzed by mathematics course. The overall test score and the score on each construct were analyzed using an ANOVA with Tukey and Games-Howell post hoc analyses. A significant difference was found in overall understanding of linear relationships across courses. The difference existed between students enrolled in the follow mathematics courses: Grade 7 Math and Algebra 2, Grade 7 Math and Geometry, and Grade 8 Math and Algebra 2. Results also highlighted a significant difference between Grade 7 Math and Algebra 2 students in all three linear relationship constructs, with Algebra 2 students scoring significantly higher than Grade 7 Math students. Overall, students did not demonstrate a strong understanding of linear relationships, although Algebra 2 students were the most successful. The area in which students in all mathematics courses showed the greatest understanding was calculating unit rates in familiar contexts (e.g. speed, units per hour). Areas of weakness included interpreting linear relationships from any representation (e.g. table, graph, equation, verbal description) and moving fluidly between representations of linear relationships. The results of this study suggested that students need to be given more opportunities to engage in learning experiences where they are interpreting multiple representations of the same linear relationship across all mathematics courses. Students should be asked to translate between tables, graphs, equations, and verbal representations of linear relationships in all directions (e.g., table to equation, verbal to equation, equation to graph). Curricular materials and learning experiences that only ask students to translate in select familiar directions between representations (e.g., table to graph, equation to graph) may be contributing to inequitable mathematics learning experiences and outcomes. Engaging in learning experiences in all directions and with all representations of linear relationships should help increase students’ conceptual understanding of linear relationships. Effectively implementing conceptual-based curricular materials along with research-based best teaching practices will help provide a more equitable mathematics experience for all students

Monosexual and Nonmonosexual Women in Same-Sex Couples’ Relationship Quality During the First Five Years of Parenthood

Research on relationship quality in same-sex couples has rarely focused on (1) couples who are parents, or (2) couples in which partners differ in sexual identity. Insomuch as nonmonosexual women (i.e., women with non-exclusive sexual orientations) experience unique challenges due to monosexism, relationship quality may be influenced by whether partners share a monosexual or nonmonosexual identity. The current study is a longitudinal, dyadic analysis of 118 female parents within 63 same-sex couples whose relationship quality (relationship maintenance, conflict, love, ambivalence) was assessed at five time points across the first 5 years of adoptive parenthood. Monosexual women were those who identified as exclusively lesbian/gay (n = 68); nonmonosexual women were those who identified as mostly lesbian/gay, bisexual, queer, pansexual, or mostly heterosexual (n = 50). Analyses revealed both actor and partner effects on maintenance and conflict, such that nonmonosexual women reported more maintenance and conflict than monosexual women, and women with nonmonosexual partners reported more maintenance and conflict than women with monosexual partners. Depression was related to greater conflict and ambivalence and less love; internalized sexual stigma was related to greater conflict and ambivalence. Maintenance and love declined over time whereas ambivalence increased during early parenthood

Older adults’ recognition of medical terminology in hospital noise

Word identification accuracy is modulated by many factors including linguistic characteristics of words (frequent vs. infrequent), listening environment (noisy vs. quiet), and listener-related differences (older vs. younger). Nearly, all studies investigating these factors use high-familiarity words and noise signals that are either energetic maskers (e.g., white noise) or informational maskers composed of competing talkers (e.g., multitalker babble). Here, we expand on these findings by examining younger and older listeners’ speech-in-noise perception for words varying in both frequency and familiarity within a simulated hospital noise that has important non-speech information. The method was inspired by the real-world challenges aging patients can face in understanding less familiar medical terminology used by healthcare professionals in noisy hospital environments. Word familiarity data from older and young adults were collected for 800 medically related terms. Familiarity ratings were highly correlated between the two age groups. Older adults’ transcription accuracy for sentences with medical terminology that vary in their familiarity and frequency was assessed across four listening conditions: hospital noise, speech-shaped noise, amplitude-modulated speech-shaped noise, and quiet. Listeners were less accurate in noise conditions than in a quiet condition and were more impacted by hospital noise than either speech-shaped noise. Sentences with low-familiarity and low-frequency medical words combined with hospital noise were particularly detrimental for older adults compared to younger adults. The results impact our theoretical understanding of speech perception in noise and highlight real-world consequences of older adults’ difficulties with speech-in-noise and specifically noise containing competing, non-speech information

Modeling Tick Populations: An Ecological Test Case for Gradient Boosted Trees

General linear models have been the foundational statistical framework used to discover the ecological processes that explain the distribution and abundance of natural populations. Analyses of the rapidly expanding cache of environmental and ecological data, however, require advanced statistical methods to contend with complexities inherent to extremely large natural data sets. Modern machine learning frameworks such as gradient boosted trees efficiently identify complex ecological relationships in massive data sets, which are expected to result in accurate predictions of the distribution and abundance of organisms in nature. However, rigorous assessments of the theoretical advantages of these methodologies on natural data sets are rare. Here we compare the abilities of gradient boosted and linear models to identify environmental features that explain observed variations in the distribution and abundance of blacklegged tick (Ixodes scapularis) populations in a data set collected across New York State over a ten-year period. The gradient boosted and linear models use similar environmental features to explain tick demography, although the gradient boosted models found non-linear relationships and interactions that are difficult to anticipate and often impractical to identify with a linear modeling framework. Further, the gradient boosted models predicted the distribution and abundance of ticks in years and areas beyond the training data with much greater accuracy than their linear model counterparts. The flexible gradient boosting framework also permitted additional model types that provide practical advantages for tick surveillance and public health. The results highlight the potential of gradient boosted models to discover novel ecological phenomena affecting pathogen demography and as a powerful public health tool to mitigate disease risks

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

More than a century of bathymetric observations and present-day shallow sediment characterization in Belfast Bay, Maine, USA: implications for pockmark field longevity

This paper is not subject to U.S. copyright. The definitive version was published in Geo-Marine Letters 31 (2011): 237-248, doi:10.1007/s00367-011-0228-0.Mechanisms and timescales responsible for pockmark formation and maintenance remain uncertain, especially in areas lacking extensive thermogenic fluid deposits (e.g., previously glaciated estuaries). This study characterizes seafloor activity in the Belfast Bay, Maine nearshore pockmark field using (1) three swath bathymetry datasets collected between 1999 and 2008, complemented by analyses of shallow box-core samples for radionuclide activity and undrained shear strength, and (2) historical bathymetric data (report and smooth sheets from 1872, 1947, 1948). In addition, because repeat swath bathymetry surveys are an emerging data source, we present a selected literature review of recent studies using such datasets for seafloor change analysis. This study is the first to apply the method to a pockmark field, and characterizes macro-scale (>5 m) evolution of tens of square kilometers of highly irregular seafloor. Presence/absence analysis yielded no change in pockmark frequency or distribution over a 9-year period (1999–2008). In that time pockmarks did not detectably enlarge, truncate, elongate, or combine. Historical data indicate that pockmark chains already existed in the 19th century. Despite the lack of macroscopic changes in the field, near-bed undrained shear-strength values of less than 7 kPa and scattered downcore 137Cs signatures indicate a highly disturbed setting. Integrating these findings with independent geophysical and geochemical observations made in the pockmark field, it can be concluded that (1) large-scale sediment resuspension and dispersion related to pockmark formation and failure do not occur frequently within this field, and (2) pockmarks can persevere in a dynamic estuarine setting that exhibits minimal modern fluid venting. Although pockmarks are conventionally thought to be long-lived features maintained by a combination of fluid venting and minimal sediment accumulation, this suggests that other mechanisms may be equally active in maintaining such irregular seafloor morphology. One such mechanism could be upwelling within pockmarks induced by near-bed currents.Graduate support for Brothers came from a Maine Economic Improvement Fund Dissertation Fellowship

In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions