Disenfranchised: How Lower Income Mothers Navigated the Social Safety Net during the COVID-19 Pandemic
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".