Beginning farmer and rancher credit usage by socially disadvantaged status

PurposeThe purpose of this paper is to examine credit usage by beginning farmers and ranchers (BFR). BFR credit usage is stratified by location (state) and by socially disadvantaged farmer and rancher (SDFR, also known as historically underserved) status. SDFR groups are defined to include women; individuals with Hispanic, Latino or Spanish Origin; individuals who identify as American Indian or Alaskan Native, Black or African American, Asian, Native Hawaiian or other Pacific Islander. Non-SDFR is defined as individuals who identify as non-Hispanic, White men.Design/methodology/approachThe US Department of Agriculture’s Census of Agriculture, Agricultural Resource Management Survey (ARMS) is linked with Farm Service Agency (FSA) loan program administrative data to estimate shares of BFR operations using FSA credit. Census data provided information on population changes in total farms and BFR operations from 2012 to 2017 which are compared by SDFR status.FindingsResults reveal differences among BFR operations active in agricultural credit markets by SDFR status and state. BFR were more common among SDFR groups as well as in regions where farms tend to be smaller, such as the Northeast, compared to a more highly agricultural upper Midwest. Among BFR, non-SDFR are more likely to utilize credit than SDFR, however, FSA appeared to be crucial in enabling BFR and especially beginning SDFR groups to access loans.Originality/valueThe results are timely and of keen interest to researchers, industry and policymakers and are expected to assist in developing and adjusting policies to effectively promote and improve BFR success in general and for beginning SDFR groups.

Mid-career Teacher Retention: Who Intends to Stay, Where, and Why?

Teacher turnover is widely understood to be among the most pressing challenges facing the American public education system. Who and where are the mid-career teachers who choose to stay in the profession? Why do they stay? Researchers need to attend to these questions to inform both national dialogue and local actions regarding how to retain and sustain mid-career teachers who positively impact student learning. This quantitative study explored mid-career teachers’ responses to the 2015–2016 National Teacher and Principal Survey to ascertain if certain demographic factors (e.g., race, school location) and school climate and teacher attitudinal factors (e.g., job satisfaction, career pathway and opportunities, support from administrators and/or sources beyond school leaders and colleagues, and influence over school policy) affect a mid-career teacher’s decision to remain in the teaching profession. Findings indicate that mid-career teachers (5 to 20 years of teaching experience) in a secondary setting are significantly more likely to intend to stay in the profession than their peers in an elementary setting, and non-White mid-career teachers (Black/African American, Asian, Native Hawaiian/Other Pacific Islanders, and Native American/Alaskan Native) than their White peers, respectively. Suburban mid-career teachers are more likely to express a desire to remain in the profession than their counterparts in urban, town, and rural settings. Related to the climate and attitudinal factors, mid-career teachers with more positive perceptions of school climate are more likely to remain in the profession. The most important factor in mid-career teacher retention is the teacher’s level of satisfaction with workplace conditions that directly impact teaching.

An Overview of an Undergraduate Diversity MCH Pipeline Training Program: USF’s Train-A-Bull

Purpose To describe an undergraduate pipeline training program (PTP) designed to guide underrepresented minorities (URM) trainees into MCH-related health professions, ultimately contributing to a diverse maternal and child health (MCH) workforce that can improve health outcomes for all women/mothers, children, and their families, including fathers and children with special healthcare needs. Description Three cohorts with 35 total undergraduate trainees were recruited to participated in the 2 years USF MCH PTP program where they were mentored, trained, guided, and supported by program faculty/staff. Students were recruited early in their education track, and the program was individually tailored based on trainees’ educational discovery stages. Key program components included seminars, summer institutes, public health courses, mentorship, internship, experiential learning opportunities, and professional networking opportunities. Assessment The majority of the undergraduate participants were diverse URMs including Hispanic/Latino (37.1%), Black/African American (31.4%), Asian (20%), and American Indian/Alaskan Native (5.7%) trainees. Out of all the cohorts, 51.4% were first-generation college students and 74.3% had economic hardships (i.e., PELL Grant, FAFSA). Resulting from the program, all cohorts increased in educational discovery stages, one-third enrolled in health-related graduate studies and half joined the MCH workforce. Conclusion Recruitment in pipeline programs should be intentional and meet students where they are in their education discovery stage. The use of educational discovery stages within a pipeline program are useful in both tailoring curriculum to individuals’ needs and assessment of progression in career decision-making. Mentoring from program staff remains an important component for pipeline programs.

Racial and ethnic disparities in COVID-19 vaccinations in the United States during the booster rollout.

Background: We sought to quantify whether there were statistically significant disparities along race and ethnicity lines during the early rollout of Covid-19 vaccine booster doses in the United States. We also studied whether such disparities replicated or widened disparities that had already been observed during the initial series rollout as of 2 months earlier (Janssen) or 6 months earlier (Pfizer-BioNTech or Moderna), which comprised the booster-eligible population. Methods: This cross-sectional study of US adults (ages ≥18 years) used public data from US Centers for Disease Control and Prevention. The observed shares of vaccine doses for each race and ethnicity were compared to the expected shares, predicted based upon the compositions of the booster-eligible and initial series-eligible populations. Results: As of November 16, 2021, 123.5 million US adults were eligible for a booster dose of either the Pfizer-BioNTech, Moderna, or Janssen vaccines. Of these, 21.7 million had received a booster dose, among whom race and ethnicity information was available for 18.8 million booster recipients. A statistically significant higher share of Non-Hispanic White and Non-Hispanic Multiple/Other race individuals had received a booster vaccination than projected based on the composition of the booster-eligible population. A statistically significant lower share of Hispanic, Non-Hispanic American Indian/Alaskan Native, Non-Hispanic Asian, Non-Hispanic Black, and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals had received a booster vaccination than expected based on the booster-eligible population. A secondary analysis of the booster-eligible population found that some of these disparities had already occurred at the time of the initial series. However, the booster campaign widened all of those disparities and added new disparities for Non-Hispanic American Indian/Alaskan Native and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals. Conclusion: Disparities in Covid-19 vaccine administration on race and ethnicity lines occurred during the initial series rollout in the US. However, these disparities were not merely replicated but widened by the early booster rollout.

Differential retention contributes to racial/ethnic disparity in U.S. academia

Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world’s largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios.

Interview with Gordon Henry

Gordon Henry is an enrolled member of the White Earth Anishinaabe Nation in Minnesota and professor of American Indian Literature, Creative Writing and the Creative Process in Integrative Arts and Humanities at Michigan State University. He is the author and co-editor of many books and collections, including The Failure of Certain Charms: And Other Disparate Signs of Life (2008). His novel The Light People (1994) won the American Book Award from the Before Columbus Foundation. Following some of the stages in his career and personal story, which he kindly accepted to share with me, this interview highlights some of the crucial key issues concerning Native American people and cultures, questions that still need a wider transnational space both inside and outside academia. Discrimination based on language has influenced the history of Native American people for centuries, starting from the forced education of the young in the 19th century and continuing in the 20th, in the context of Hollywood film productions. Linguicism, language-based racism (Phillipson 1992), is a topic that needs to be addressed in the light of the recent flourishing of extremist thought worldwide, which carries the abused rhetoric of ‘us vs them’ (van Dijk 2015) and, at the same time, spurs protest movements. This reflection goes hand-in-hand with the controversial topic of the appropriation of Native American cultural practices by old and new wannabes (non-people who are so much fascinated by Native American cultures that end up imitating them by, for example, choosing a Native name or emphasising certain aspects of the culture which they admire, often basing their beliefs on stereotypes), whilst people living in the Reservations are still neglected and the Native American and Alaskan Native population register extremely high suicide, homicide and alcoholism rates compared to the U.S. all races population (especially women). But, the efforts and educational programs aimed to preserve languages and cultures (like the Lakota Language Consortium or the Rosetta Stone Endangered Language programs), the vibrancy of the artistic scene in the visual, literary and music fields, the various forms of activism and community engagement projects (such as, for example, the MMIWG movement – Missing and Murdered Indigenous Women and Girls – the water protectors protest at Standing Rock, known as #NoDapl, or the prayerful journey called Run4Salmon in California) are also to be acknowledged as milestones in the process of regaining self-sovereignty by Native people. Against the background of these considerations, I am pleased and honoured to share thoughts, feelings and emotions with Gordon Henry.

Financial Hardship Amongst Patients with Hematologic Malignancies: Using the EMR to Streamline and Prioritize Patient-Centered Care

Background: Self-reported financial hardship (FH) amongst cancer patients is increasingly becoming a challenge for patients, caregivers, and healthcare providers. FH not only leads to financial struggles, significant lifestyle changes, and emotional distress, but also contributes to treatment noncompliance, affecting clinical outcomes. As treatment costs rise, it is crucial to develop efficient methods to proactively identify and alleviate FH in hematology practice. One potential approach is utilizing automated processes to identify those at highest risk of FH. At Mayo Clinic, screening for FH involves using a single financial strain question 'How hard is it for you to pay for the very basics like food, housing, medical care, and heating?' which all cancer patients answer annually as part of the institution's Social Determinants of Health (SDOH) assessment. Answers are on a five-point scale including not hard at all, not very hard, somewhat hard, hard, and very hard. In this study, we assess the prevalence and predictors for FH (denoted by a response of "Very hard" "Hard" or "Somewhat hard") amongst the Mayo Clinic hematologic malignancy patient population. Our study objective was to determine if this automated process could identify those at risk for FH. Methods: Patients who received care for hematologic malignancies (lymphoma, leukemia, plasma disorders, myelodysplastic/myeloproliferative disorders, and other heme malignancies) at any of the Mayo Clinic cancer centers (Minnesota, Arizona, and Florida) and who had completed the SDOH screen at least once were included in this study. The electronic medical record (EMR) and Mayo Clinic Cancer Registry were utilized to extract demographic and disease variables. Patient's home zip code was used to determine rural/urban residence, distance from cancer center, and the Area Deprivation Index (ADI), a measure of socioeconomic disadvantage based on home zip code (ranging from 1-100, with 100 representing the most disadvantaged). Multivariable logistic regression modeling was used to examine predictor variables for FH in this patient population. Results: The final cohort included 10,024 patients from 2018 to 2020. Median age was 64.6 years (IQR 58.1,73.7), 58% were male, and 79% married. Race/ethnicity composition was 94% White (n=9,268), 2.5% Black (n=246), 0.4% American Indian/Alaskan Native (44), and 4% Hispanic (n=360). Fifty-six percent of patients had Medicare and 41% had commercial insurance. Fifty percent were retired, 40% were working/students, and 72% were urban residents. Mean ADI was 41.2. Fifty-six percent of patients had lymphomas, 23.5% had plasma cell disorders, 8.5% had leukemias, 6.8% had other hematological malignancies, and 5.5% had myelodysplastic/myeloproliferative neoplasms. FH was reported by 12.8% (n=1286) of the patients. Table 1 shows the results of the multivariable model. A significantly higher likelihood of endorsing FH was noted in Hispanic vs non-Hispanics, Black and American Indian/Alaskan Native groups vs whites, Disabled/Unemployed vs working, Medicaid, Medicare, and Self-Pay groups vs commercial insurance, higher ADI (5 th quintile vs 1 st), and myelodysplastic/myeloproliferative disorder and other hematologic malignancy vs lymphoma patients. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Conclusion: Our study used automated data extraction from the EMR to efficiently identify predictors of FH in hematologic cancer patients. Employing a dichotomized and automated "flag" for FH, particularly if incorporated in the EMR, could ease the identification of SDOH issues, facilitate timely connection to appropriate resources, and help provide better patient-centered care. Figure 1 Figure 1. Disclosures Ailawadhi: Sanofi: Consultancy; Cellectar: Research Funding; Karyopharm: Consultancy; Ascentage: Research Funding; Genentech: Consultancy; Janssen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Beigene: Consultancy; GSK: Consultancy, Research Funding; AbbVie: Consultancy; Medimmune: Research Funding; Pharmacyclics: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Xencor: Research Funding. Fonseca: OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; BMS: Consultancy; Mayo Clinic in Arizona: Current Employment; Aduro: Consultancy; AbbVie: Consultancy; GSK: Consultancy; Merck: Consultancy; Juno: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Novartis: Consultancy; Bayer: Consultancy; Celgene: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy. Griffin: Exact Sciences: Research Funding.