Disenfranchised: How Lower Income Mothers Navigated the Social Safety Net during the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Government programs and other forms of assistance act as critical safety nets in times of crisis. The federal government’s initial response to coronavirus disease 2019 represented a significant increase in the welfare state, but the provisions enacted were not permanent and did not reach all families. Drawing on interviews with 54 lower-income mothers and grandmothers, we analyze how families navigated the safety net to access food during the pandemic. Pandemic aid served as a critical support for many families, but participants also described gaps and barriers. Following the argument that food is a basic human right, we identify how mothers encountered three forms of disenfranchisement: being denied or experiencing delayed public benefits, being afraid to access assistance, and receiving paltry or inedible emergency food. We conclude by arguing for an expanded social safety net that broadens access to necessary food resources before, during, and after crises such as the coronavirus disease 2019 pandemic.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.020 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it