Navigating food access and distribution during the pandemic
Bibliographic record
Abstract
COVID-19 increased food insecurity among African Americans. However, little is known about the impact of COVID-19 on food access and delivery for this population in Cuyahoga County. The objective of this study was to collect insights into the facilitators of and barriers to food access and delivery from community stakeholders. Methods: A total of 10 in-depth individual interviews with community stakeholders were conducted. Content analysis was used to analyze the interviews. Results: COVID-19 led to immediate and necessary changes to food access and distribution practices. Additionally, the increased utilization of food pantries, limited food supply, and lack of transportation to food pantries were identified as challenges to food access and distribution. However, community stakeholders were able to continue serving the community despite food supply and distribution challenges. Conclusion: This study provided novel insights into the challenges faced by community stakeholders and strategies that can be used to overcome these food dissemination challenges during the COVID-19 pandemic. Nurses can play a key role in addressing food insecurities in African American communities through nursing assessments and advocacy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".