Conditions that Shape Thriving
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This section highlights several high-level conditions that shape economic well-being for women and girls, alongside key barriers identified through both data and community insight. Together, these measures look beyond income alone to consider how people get to work, how mental health affects daily life, and whether household resources are sufficient to meet basic needs. These are all measures that the Community Cohort identified as important indicators of or barriers to thriving across multiple sections in this report. Throughout this section, quantitative trends are paired with reflections from the Community Cohort to ground the data in lived experience. This combined approach helps illustrate not only where disparities exist but also how women, girls, and families navigate challenges with resilience amid structural constraints.
Key Findings from the Community Cohort
The Community Cohort (Cohort) is a group of local women and people whose lived experiences reflect womanhood—especially Black and Latine parents—who helped shape this report by sharing their real-life experiences, priorities, and interpretations so the data reflects what thriving (and struggling) actually looks like in our community.
The cohort expressed concern about the bus system, given how many people walk to work and how few people use the bus. They were particularly concerned about the percentage of older people who reported walking to work.
Frequent mental distress seems to be a relatively common experience across a fairly diverse geography, but females experience it more than males.
- 19% of females report frequent mental distress, compared to 12% of males.
- Residents between 35 and 44 seem to have had a recent increase in reports of frequent mental distress, and residents experiencing poverty have higher rates of frequent distress.
- Renters report higher rates of frequent mental distress than homeowners, leading cohort members to observe, “I think everyone knows it, but your housing situation really changes how you feel about things,” and “If you don’t have a reliable place, it weighs on you.”
The rates of some kinds of Emergency Department visits for mental health concerns increased a lot around 2021 and 2022, particularly for youth.
- This led cohort members to note, “It looks like our young folks, well they are not doing well,” and that they’re “becoming increasingly unwell over the years. Like, if you look at the 2017-2022 time frame, suicidal ideation has really went rampant.”
Females generally have higher rates of Emergency Department usage for mental health diagnoses, with the exception of suicidal ideation.
- The cohort noted that women who are navigating the postpartum period may be at a particular risk for mental health challenges. “I know that there’s not a whole lot of education and support around postpartum depression and the way it manifests. I feel like that might be a helpful piece of the puzzle here.”
- Non-Hispanic residents generally have higher rates of Emergency Department usage for mental health diagnoses than Latine residents.
- Black and white residents generally have similar rates of Emergency Department usage for mental health diagnoses, but Black residents have higher rates of ED use for depression and trauma / stressors than white residents.
- The cohort also noted that LGBTQ+ residents have higher rates of suicidal ideation and suicide, but sexual orientation and gender identity data were not included in the Emergency Department data.
When observing the high rate of residents who are income insufficient, the cohort noted that a lot of families make it work, even if the estimates indicate that they should not be able to, highlighting the resiliency of local community members.
- They also raised concerns about the impact of student loans on financial security, even in households that appear to have sufficient income.
- They also pointed out that older residents may have dramatically different experiences of income insufficiency by race/ethnicity.
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Commuting to Work
This indicator measures the percentage of workers who use various methods to commute to work.
The Community Cohort felt it was important to provide information about commute times by mode of transportation and whether or not workers have access to a vehicle in their household. A graph of median travel times to work by mode of transportation and vehicle access between 2019 and 2023 can be found below.
Please note that in some cases, the margins of error on this graph are high or could not be estimated, potentially due to small sample sizes. In this case, readers should use caution in interpreting the results. This graph also does not include students or other residents living in group quarters.
Data Visualization
Median Travel Times to Work by Mode of Transportation and Vehicle Access (2019-2023)
The cohort also raised questions about how TransAID users would be described in this measure. The survey this data comes from asks residents to describe their commute themselves using the categories provided, choosing from options that include “Car, Truck, or Van”, “Bus”, or “Other method”. Individual TransAID users may have selected different responses to this question.
Data Visualization
Percent of Residents Commuting to Work by Mode of Transportation (5-year Periods from 2015-2019 to 2019-2023)
Community Voices
Transportation further stretches her wages; without a car, she relies on ride‑shares and favors, explaining that she is “catching Ubers and Lyfts and everything else” just to manage daily life.
Data Notes
Commuting to Work
Data Notes
- This indicator only includes employed people and focuses specifically on how people commute to work. Some people may use different modes of transportation for work and other travel.
- This indicator only includes employed people and focuses specifically on how people commute to work. Some people may use different modes of transportation for work and other travel.
- Cohabitating couples are not included as Married or Cohabitating before 2015-2019.
- Members of cohabitating couples who are not the householder or partnered with the householder may be mislabeled as not cohabitating. For example, if two unmarried couples are living together as roommates, only the householder and their partner would be counted. This may underestimate cohabitating partners.
- The Census Bureau did not include same-sex married couples as married couples in their data until the 2015-2019 data.
- There is generally a statistically significant difference in the percentage of white, non-Hispanic workers taking the bus to work and Black and Latine workers. The difference in the percentage of Black and Latine workers is not statistically significant. The same is true for working from home.
- There is generally a statistically significant difference between the percentage of all race/ethnic groups driving to work.
- There is generally a statistically significant difference between the percentage of white, non-Hispanic workers who walked to work and the number of Black workers who walked to work, but the differences between other groups are not statistically significant.
- The percentage of males and females who work from home is generally statistically significant, but no other modes of transportation had statistically significant differences by sex.
- The percentage of Black males and females commuting by bus is generally statistically significantly different than the percentage of white, non-Hispanic males and females, but no other bus differences were statistically significant. There were some statistical differences for other commuting modes, but analysts were not able to identify clear patterns.
- The percentage of workers in households headed by single females with no spouses present taking the bus to work is generally statistically significantly different than workers from other household types. The difference between workers in single female headed households and married couple headed households walking to work is generally statistically significant. The difference in the percentage of workers working from home in households headed by single men is significantly different from those in households headed by married couples.
- Workers in households headed by same-sex married or cohabitating couples did have a statistically significant change in the percentage of workers commuting by car over time, and that percentage is statistically significantly different from other households in later years. There was also a difference over time for the percentage of workers from these households working from home, but it was only significantly different from workers from some other household types in later years.
- 18-34 year old workers generally take the bus to work and work from home at rates that are significantly different from older age groups.
- Workers over 65 generally drive to work at rates that are significantly different from other age groups.
- With the exception of walking to work, there are generally not statistically significant differences in mode of transportation to work for workers with and without children in their households.
- The apparent difference in the percentage of workers without vehicles taking cars to work over time is not statistically significant.
- There are generally statistically significant differences in the percentage of workers with and without vehicles taking the bus to work, taking a car to work, walking to work, and working from home.
- Data on household type and presence of children was not tested for statistical significance because of similarities to other breakdowns
Data Sources
- American Community Survey (ACS) 2019-2023 5-year data
Citations
- U.S. Census Bureau. (2025). American Community Survey (ACS), 5-year public use microdata sample (PUMS), 2019–2023. https://www.census.gov/programs-surveys/ acs/microdata.html
Frequent Mental Distress
This indicator measures the percentage of residents in the Piedmont Region of North Carolina who reported frequent mental distress. Residents were identified as having frequent mental distress if their mental health was “not good” for 14 or more days out of the past 30 days.
Respondents reporting that their mental health was not “not good” for 14 or more days answered the question: “Now thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?”
The data in this measure describes the Piedmont Region of North Carolina, not just Forysth County. The counties included in this geography are: Alamance, Alexander, Anson, Cabarrus, Caswell, Catawba, Chatham, Cleveland, Davidson, Davie, Durham, Forsyth, Franklin, Gaston, Granville, Guilford, Iredell, Lee, Lincoln, Mecklenburg, Montgomery, Moore, Orange, Person, Randolph, Richmond, Rockingham, Rowan, Stanly, Stokes, Union, Vance, Wake, Warren, and Yadkin counties.
Data Visualization
Percent of Piedmont Region Residents Reporting Frequent Mental Distress (2018-2023)
Community Voices
Youth who have already experienced years of complex trauma are often then exacerbating their pre-existing trauma-induced mental health symptoms as they enter adulthood. Youth who have aged out of foster care report higher rates of depression, trauma exposure and behavioral health challenges than their peers who did not experience foster care. They may have had years of therapy to work through the healing process of previous traumas. Oftentimes, this state in life can reactivate the effects of earlier trauma. Threats of uncertainty, fear of failure, and mistrust of others can lead to chronic stress and hyperarousal of a number of physical and emotionally trauma induced symptoms. Questions such as, “Does anyone see me? Is anyone there for me? Where do I belong?” may echo in the deep corners of their minds even if they never say them outloud. Neurologically, their brains know it. Physically, their bodies can feel it. They may then react in ways that are unexpected, even for them. They may not know what they feel or why they respond the way they do. Their trauma responses are compounded during this critical developmental stage and emotional regulation and decision-making become extremely challenging.
Data Notes
Frequent Mental Distress
Data Notes
- This indicator reflects responses from the Piedmont Region of North Carolina, which includes Forsyth County.
- Data was not available for some demographic groups in some years.
- Differences for the total population over time are not statistically significant, but changes over time for females are.
- Differences by sex are generally statistically significant, but differences by race/ethnicity generally are not.
- Residents over 65 are generally significantly different from younger residents.
- College graduates are generally statistically significantly different from those with lower levels of education.
- Differences over time for residents with different levels of education are generally statistically significant.
- Differences between higher-income and lower-income residents are generally statistically significant.
- The 2023 rates are statistically significantly different from earlier rates for higher-income groups.
- Rates were significantly different between those with and without disabilities across all time periods, and rates were different over time for those with and without disabilities.
- Homeowners generally have different rates than those who rent or have other housing arrangements over time.
- Differences over time are generally not significant by housing type.
Data Sources
- NC Division of Public Health. State Center for Health Statistics. Behavioral Risk Factor Surveillance System (BRFSS) 2018-2023.
Citations
NC Division of Public Health. (n.d.). BRFSS 2018-2023 – Piedmont North Carolina: Healthy Days – Frequent Mental Distress (within the past 30 days). NCDHHS, NC Division of Public Health, State Center for Health Statistics. https://schs.dph.ncdhhs.gov/data/brfss/index.html
Mental Health Emergencies
This indicator measures the number of emergency department visits for mental health-related conditions in Forsyth County per every 10,000 residents for all of the breakdowns except insurance. The insurance breakdown shows the percentage of visits paid for by each type of insurance. A visit is considered mental health-related if a patient presents with any of the following issues:
- Anxiety
- Depression
- Self-Inflicted Injury
- Suicidal Ideation
- Trauma / Stressors
The Community Cohort had questions about what was included under the category of “Trauma / Stressors” and whether or not it included sexual assault. This category included severe stress in response to life events (e.g. Post-traumatic stress disorder), dissociative disorders in which a patient loses memories, awareness and/or control of their body, and disorders of social functioning. It is possible that sexual assault could trigger one of these responses, resulting in a diagnosis in this category, but the sexual assault itself would not be classified in this category.
The cohort also had questions about how race categories were assigned in the emergency department data. North Carolina state statute indicates that patients should report their own race and ethnicity, but it is not possible to know if this happens in practice. The researchers who created this dashboard also noted that the “other” category includes multi-racial residents as well as those from smaller racial and ethnic groups. They noted that this may not line up with how the population data they used to calculate rates assigned “other”, and that this may contribute to some of the data for “other” races looking unusual.
Lastly, the cohort requested information about the percentage of emergency department visits that are covered by different kinds of insurance as context. According to UNC’s Sheps Center for Health Services Research, across North Carolina, the percentage of emergency department visits by insurance type is as follows:
- Commercial Insurance/HMO: 38%
- Medicaid: 23%
- Medicare: 14%
- Other Government: 4%
- Uninsured: 21%
- Other: 1%
Data Visualization
Rate of Emergency Department Visits with Mental Health Diagnoses per 10,000 Residents (2017-2023)
Data Visualization
Percent of Emergency Department Visits with Mental Health Diagnoses by Insurance Type (2017-2023)
Community Voices
Experiencing mental health struggles at such a young age made me more aware of the silent battles others face. I became more compassionate, more patient, and more intentional about supporting people around me. I developed a heart for helping others with their mental health because I know what it feels like to be overwhelmed and misunderstood.
Now, at sixteen years old, I know that I want to become a therapist. This dream was born from my own experiences. I want to be the person who listens, who creates a safe space, and who reminds others that their feelings matter. I want to help break the stigma surrounding mental health, especially in the Black community, where these conversations are often avoided… My story is proof that strength and vulnerability can coexist, and that healing is not a weakness, but an act of courage.
LGBTQ+ people of color sit at the sharpest intersections of these realities.
They face the combined effects of racial inequity, economic precarity, and anti-LGBTQ+ discrimination. In Forsyth County, where racial disparities in wages, housing, and health outcomes are already well-documented, queer and trans people of color often experience the most severe consequences of policy gaps and institutional neglect. Job loss hits harder without generational wealth. Housing instability is more dangerous when racism shapes interactions with landlords or law enforcement. Mental health struggles deepen when affirming, culturally competent care is scarce or inaccessible.
These are not anomalies. They are predictable outcomes of systems that were not designed with LGBTQ+ lives in mind.
Data Notes
Mental Health Emergencies
Data Notes
This data has not been adjusted for age. If the prevalence of these mental health diagnoses is different across different age groups, some apparent demographic differences may reflect differences in the ages of the population.
Data Sources
- NC DETECT Mental Health Dashboard, UNC-Chapel Hill and the NC Division of Public Health
Citations
- The University of North Carolina at Chapel Hill. (n.d.). Mental health dashboard | NC DETECT. NC DETECT. https://ncdetect.org/mental-health-dashboard/
- Collection and reporting of race and ethnicity data, North Carolina General Statutes SL 2024-58 § 130A-16. https://www.ncleg.gov/EnactedLegislation/Statutes/PDF/BySection/Chapter_130A/GS_130A-16.pdf
- NC Department of Health and Human Services, Division of Public Health and UNC School of Medicine. (n.d.). Emergency department syndrome & custom event definitions. NC Detect. https://ncdetect.org/case-definitions/
- World Health Organization. (n.d.). ICD-10 Version:2016. World Health Organization. https://icd.who.int/browse10/2016/en
- A. Isling, personal communication, December 15, 2025.
- Lees, E. (n.d.). Emergency Department Visits (Treat and Release) – Patient Characteristics Summary Data for All Hospitals. Winston-Salem; The Cecil G. Sheps Center for Health Services Research, UNC.
Income Insufficiency
This indicator measures the percent of the Forsyth County population who live in households that do not have enough income to meet their estimated annual living expenses (e.g., housing, health care, food, etc.). That is, the percentage of the population that is income insufficient. This measure compares the cost of these expenses for different families in Forsyth County and compares their income to these expenses. It is not based on a particular minimum or living wage standard.
In responding to how high these rates are in Forsyth County, the Community Cohort expressed admiration that so many families succeed in keeping their families fed and housed, even with limited resources.
The Asset Building Coalition of Forsyth County uses this measure to estimate a living wage for Forsyth County. In 2026, they are promoting $26 an hour as a living wage. They estimate that this is the hourly rate that would be needed to cover basic living expenses for at least 75% of working adults 18-65 in Forsyth County if they are working full-time, year-round.
Data Visualization
Percent of Residents with Insufficient Income (2023)
Community Voices
Queer, trans, and gender-expansive people often face extraordinary financial barriers to forming families: through adoption, fertility care, legal parentage, or simply securing safe housing and employment stable enough to imagine a future. These costs exist alongside persistent wage gaps, employment discrimination, and uneven access to benefits. What is framed socially as “choice” is often constrained by policy, price, and prejudice.
The result is a doubling of burden: lower wages paired with higher costs, fewer safety nets paired with greater risk.
For LGBTQ+ people, especially those who are single or not cohabitating, economic vulnerability may look different, but it is no less real. Survival often relies on chosen family, informal support networks, or navigating workplaces and housing markets where safety, dignity, and belonging are not guaranteed. Mental health, economic security, and housing stability become intrinsically intertwined when you are absorbing risk alone.
Across interviews, participants describe wages that sustain survival but not security. Income is consistently “just enough” to keep households afloat, but not enough to allow savings, rest, or recovery when life changes. No one blames themselves; women describe careful, disciplined budgeting nested inside systems that steadily absorb income through fixed costs, debt, caregiving demands, and workplace practices.
She and her partner “do everything right”—tight budgeting, strategic grocery shopping, avoiding extras, prioritizing debt—but still cannot see a path to savings. As she puts it, she doesn’t know “how anyone’s supposed to save” and feels that “everyone’s kind of bleeding dry at this point.” In her story, wage inadequacy is not about mismanagement; it is about systems that leave no margin for emergencies, rest, or future planning.
Across the dataset, women describe high‑interest car loans taken when credit scores were low, student loan payments that resume after forbearance, and medical or other debts that absorb what little flexibility their earnings might otherwise provide. Even when bills are technically paid, women ask how they are supposed to ever save.
Data Notes
Income Insufficiency
Data Notes
- These numbers are based on general estimates of expenses; individual costs may be higher or lower.
- The Census Bureau considers everyone who lives together to be a “household”. These people may not always share expenses or responsibilities for children. cohabitating couples are not included as married or cohabitating before 2015-2019.
- Members of cohabitating couples who are not the householder or partnered with the householder may be mislabeled as not cohabitating. For example, if two unmarried couples are living together as roommates, only the householder and their partner would be counted. This may underestimate cohabitating partners.
- The Census Bureau did not include same-sex married couples as married couples in their data until the 2015-2019 data.
- The apparent difference by sex of adults is not statistically significant.
- The income insufficiency rates of white, non-Hispanic residents is significantly different from that of Black and Latine residents, but the rates for Black and Latine residents are not different from each other.
- These same race and gender patterns exist when disaggregating by race/ethnicity and sex of adults together.
- The rate of income insufficiency for those under 18 is significantly different from all other age groups, but those age groups are not significantly different from each other
- The rate of income insufficiency for residents living in households headed by married couples is significantly different than those in households headed by male and female householders with no spouse present.
- The rate of income insufficiency for residents living in households headed by married or cohabitating opposite-sex couples is significantly different than that of residents living in households headed by householders with no partner present, regardless of the sex of the householder. Residents living in households headed by same-sex married or cohabitating couples only had significantly different rates of income insufficiency than those living in households headed by a female householder without a partner. Residents living in households headed by a single female without a partner had significantly different rates of income insufficiency than those in all other household types.
- Residents in households headed by single females and married couples had significantly different income insufficiency rates when comparing households with and without children. Those living in households headed by single men did not.
- Among residents with children in their households, those living in households headed by single women had significantly different rates of income insufficiency than those in other households.
- Among residents with no children in their households, those living in married couple households had significantly different rates of income insufficiency than those living in households headed by single people.
- Estimates for the rates of income insufficiency for those living in households headed by males without a partner with children present may be unreliable.
- Estimates for the rates of Hispanic or Latine Male householders with no spouse present may be unstable.
- The rate of income insufficiency for residents in households headed by single Black females is significantly different from that of those living in households headed by Black married couples. This difference is not statistically significant for residents living in households headed by Latine householders, but residents in households headed by Latine males have significantly different rates of income insufficiency than those headed by Latine married couples.
- Residents living in households headed by white, non-Hispanic married couples have significantly different rates of income insufficiency than those headed by other white, non-Hispanic residents.
- Residents living in households headed by married couples have significantly different rates of income insecurity depending on the race/ethnicity of the householder. The rate of income insufficiency for residents living in households headed by a white, non-Hispanic, single female householder is significantly different from households headed by single females of other races/ethnicities. Residents living in households headed by white, non-Hispanic single male householders had significantly different rates of income insufficiency than those living in households headed by Black single male householders, but residents living in households headed by Black and Latine single males did not have significantly different rates of income insufficiency from each other.
- The rate of income insufficiency for residents working less than 35 hours or less than year-round was higher than that of residents working at least 35 hours a week year-round, but the percentage of residents working year-round for 35 to 45 hours a week was not significantly different than the percentage of residents working for more than 45 hours a week year-round.
- The margin of error for the percentage of Hispanic or Latine residents 65 and over is high relative to the estimate.
- Across age groups, white, non-Hispanic residents generally have statistically significant differences in the income insufficiency rate than Black and Latine residents. Differences between Latine and Black residents in the same age group are not always statistically significant.
Data Sources
- American Community Survey (ACS) 2023 1-year data
| Expense Category | Source Name(s) | Source Institution(s) | Geographic Level |
| Child Care | North Carolina Child Care Market Rate Study | NC Department of Health and Human Services (NC DHHS) | County |
| Annual Price of Child Care Report | ChildCare Aware of America | State | |
| Food | Low-Cost Food Plan | US Department of Agriculture (USDA) | Region |
| Health Care | Consumer Expenditure Survey (CES) | Bureau of Labor Statistics (BLS) | Region |
| Health Insurance | Consumer Expenditure Survey (CES) | Bureau of Labor Statistics (BLS) | Region |
| Housing | Fair Market Rents (FMR) | US Department of Housing and Urban Development (HUD) | County |
| Savings | Household Income from Public Use Microdata Sample (PUMS) | U.S. Census Bureau American Community Survey (ACS) | County |
| Transportation | Consumer Expenditure Survey (CES) | Bureau of Labor Statistics (BLS) | Region |
| Taxes | Federal and State Tax Codes / TAXSIM | US Congress / TAXSIM | National and State |
| Other Expenses | Consumer Expenditure Survey (CES) | Bureau of Labor Statistics (BLS) | Region |
Citations
- Bureau of Labor Statistics. (2024, August 7). Consumer Expenditure Survey (CES) Data Tools and Tables. U.S. Department of Labor. https://www.bls.gov/cex/data.htm
- Bureau of Labor Statistics. (2024, May 13). Consumer Expenditure Survey Glossary. https://www.bls.gov/cex/csxgloss.htm
- Bureau of Labor Statistics. (2025). Consumer Expenditure Survey (CES) Homepage. https://www.bls.gov/cex/
- Bureau of Labor Statistics. (2025). Gasoline (All types) in U.S. city average, all urban consumers, not seasonally adjusted [CPI series ID: CUUR0000SETB01]. https://data.bls.gov/timeseries/CUUR0000SETB01?output_view=pct_12mths
- Bureau of Labor Statistics. (2025). Medical care in U.S. city average, all urban consumers, not seasonally adjusted [CPI series ID: CUUR0000SAM]. U.S. Department of Labor. https://data.bls.gov/timeseries/CUUR0000SAM?output_view=pct_12mths
- Bureau of Labor Statistics. (2025). Consumer Expenditure Survey Tables by Age of Reference Person and Consumer Unit Size. https://www.bls.gov/cex/tables.htm
- Child Care Aware of America. (n.d.). Child Care at a Standstill: Price and Landscape Analysis 2023. https://www.childcareaware.org/thechildcarestandstill/
- Feenberg, D. R., & Coutts, E. (1993). An introduction to the TAXSIM model. Journal of Policy Analysis and Management, 12(1), 189–194. https://doi.org/10.2307/3325474
- National Bureau of Economic Research. (2022, May 20). TAXSIM version 35: NBER’s federal and state income tax simulator. https://taxsim.nber.org/taxsim35/
- North Carolina Department of Health and Human Services. (n.d.). Market Rates for Child Care Subsidy. https://ncchildcare.ncdhhs.gov/Home/DCDEE-Sections/Subsidy-Services/ Market-Rates
- Orr, S. (n.d.). usincometaxes: Calculate federal and state income taxes in the United States (R package v0.7.1). https://cloud.r-project.org/web/packages/usincometaxes/index.html
- United States Department of Agriculture (USDA), Center for Nutrition Policy and Promotion. (2025, May 23). USDA Food Plans: Monthly Cost of Food Reports https://www.fns.usda.gov/ research/cnpp/usda-food-plans/cost-food-monthly-reports
- U.S. Bureau of Labor Statistics. (2025, March 21). Consumer Price Index: R-CPI-U-RS Homepage. https://www.bls.gov/cpi/research-series/r-cpi-u-rs-home.htm
- U.S. Census Bureau. (2024). American Community Survey (ACS), 1-year public use microdata sample (PUMS), 2023. https://www.census.gov/programs-surveys/ acs/microdata.html
- U.S. Department of Housing and Urban Development. (n.d.). Fair market rents dataset. HUD User. https://www.huduser.gov/portal/datasets/fmr.html
- U.S. Department of Housing and Urban Development. (2018, August). Proposals to Update the Fair Market Rent Formula (p. 1, footnote 2). https://www.huduser.gov/portal/sites/default/ files/pdf/Proposals-To-Update-the-Fair-Market-Rent-Formula.pdf
- V. Pérez Chandler, personal communication, December 12, 2025.