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The Effects of Polycystic Ovarian Syndrome (PCOS) on Pregnancy from a Nursing Perspective
Full text linkThe purpose of this research is to investigate the effects of Polycystic Ovarian Syndrome on pregnancy from a nursing standpoint. Nearly 5-10% of women in the United States are affected by polycystic ovarian syndrome during the reproductive years. This research aims to investigate how this condition impacts fertility and pregnancy risks. This initial research was completed through a review of existing literature accessed through databases such as CINNAHL and PubMed. Once all data is collected, the goal is to seek nursing interventions to lessen the effects of polycystic ovarian syndrome and increase positive pregnancy outcomes. This research is critical as there is a deficit in research regarding polycystic ovarian syndrome and how nurses can better support these patients
Men’s Preconception Health: Impact on Pregnancy and Awareness Strategies.
Full text linkMen’s preconception health plays a critical role in pregnancy outcomes, but it continues to be overlooked in healthcare education. While women are routinely counseled by OBGYN providers on how nutrition, lifestyle, and chronic conditions can affect fertility, men often receive little to no guidance from their primary care providers. This project uses a literature review to look deeper into how limited awareness and involvement in men’s preconception health may impact pregnancy and infant health outcomes. The gap is linked to cultural norms, healthcare practices, and the lack of clear resources for men. This research aims to develop strategies that promote awareness and clarity for both parents. The goal is to include paternal preconception health education into primary healthcare visits and public health efforts to improve future outcomes for families
Labor and Residence within the Mexican Community in Aurora, Illinois, 1920-1940.
Full text linkThis research examines how labor opportunities in Aurora, Illinois, between 1920 and 1940 shaped the growth and development of the Mexican community. Using U.S. census data from 1920, 1930, and 1940, historical city maps, oral histories, and special agent reports, the project traces employment patterns across three distinct waves of migration. It explores the role of industries such as the Chicago, Burlington & Quincy Railroad, the Cotton Mill, and New Deal initiatives like the Works Progress Administration (WPA) and National Youth Administration (NYA) in the formation and growth of the Mexican community. The findings reveal that labor not only shaped economic stability but also influenced residential patterns, community cohesion, and generational settlement in Aurora. The study highlights how those without ties to the railroad or other labor sectors began settling farther from the center, illustrating how employment patterns influenced the community’s spatial organization. By uncovering these early developments of the Mexican community in Aurora, this research contributes to broader discussions of Mexican migration in the Midwest and reflects on the intersections of race, labor, and urban development in twentieth-century America
Avoiding Dupe Process
Full text linkAdvances in artificial intelligence (AI) combined with increased documentation of human overreliance on AI recommendations demands a reexamination of content moderation processes. Social media platforms—reacting to internal values, social pressure, regulatory mandates, or some combination of all three—have carried over procedural due process norms to content decisions. One common procedural protection is a “human-in-the-loop” (HITL) requirement. These requirements insist that a human provide some oversight role prior to an automated decision becoming final.
A review of the core values of due process—namely, accuracy, fairness, legitimacy—and the nature of hybrid decisional frameworks—those that involve AI and human inputs—show that HITL requirements likely result in less accurate, less fair, and less legitimate decisions. This conclusion suggests that platforms have two ways forward: either rely exclusively on human content moderation processes or AI-driven processes with human review at the systemic rather than post-by-post level. Because the former is impossible, this Article focuses on the latter. The appropriateness of AI moderation is confirmed by application of a version of Mathews balancing, modified for the content moderation context.
The Article makes three important points in this ongoing, controversial topic. First, widespread and ensuring automation bias among moderators means that HITL requirements actually decrease accuracy. Second, HITL requirements render the content moderation less legitimate by knowingly and unnecessarily subjecting humans to continued exposure to mentally and physically damaging content. Third, definitively stating that due process does not require a HITL in individual content moderation decisions
Reimagining Traditional Education Through Humanizing Models of Personalized Learning: Examining Implementation in the Midwest
Full text linkABSTRACT
REIMAGINING TRADITIONAL EDUCATION THROUGH HUMANIZING MODELS OF PERSONALIZED LEARNING: EXAMINING IMPLEMENTATION IN THE MIDWEST
Laura Garland, EdD
Department of Curriculum and Instruction
Northern Illinois University, 2025
Michael Manderino, Director
This qualitative document analysis, supported by semi-structured interviews, investigated the ways in which three Midwestern, K-12 public school districts implemented humanizing models of personalized learning, as a method of shifting from a traditional, teacher-centered instructional paradigm to a learner-centered one. Additionally, it sought to identify how the pedagogical attributes employed in participant districts explicitly and implicitly aligned with humanizing pedagogies. Participant districts were chosen based on their relationship with the Institute for Personalized Learning, as well as their district-wide implementation approach.
Findings revealed a high level of consistency between the implementation plans employed across all participant districts, as well as alignment between district pedagogical attributes and several principles of humanization. However, all participant districts were found to fall short of fully aligning their models of PL to that of a humanizing pedagogy. While progress toward implementing humanizing models of PL, as a means of reimagining traditional education, was noted, disparities persist. Based on these findings, leaders seeking revolutionary transformation within public school districts, through the implementation of humanizing models of PL, should ensure that a strong, strategic foundation is developed in which a learner-centered, humanizing philosophy underlies all district-wide, systemic shifts. Additionally, classroom teachers should focus on the holistic development of students, ensuring not only that they learn the prerequisite skills and dispositions necessary to drive their own learning but that they are supported in using their skills to critically reflect on the world around them and act against inequities
