Predictors of Food and Water Stockpiling During the COVID-19 Pandemic Among Latinos and Non-Latino Black People
Bibliographic record
Abstract
OBJECTIVE: The study examined factors associated with food and water stockpiling (FWS) during the COVID-19 pandemic. METHODS: A secondary analysis of online survey data collected in two waves: April 2020 (wave 1) and June/July 2020 (wave 2), was conducted through REDCap web application. A total of 2,271 Non-Latino Black and Latino adults (mean age: 36.8 years (SD = 16.0); 64.3% female) living in Illinois were recruited. Participants self-reported if they stockpiled food and/or water (FWS) seven days prior to survey completion because of the pandemic. Logistic regression was used to determine if each variable was associated with the odds of reporting FWS. RESULTS: Nearly a quarter (23.3%) of participants reported FWS. The adjusted model revealed that odds of FWS increase as the number of household members increased (OR: 1.21; 95% CI: 1.05-1.41). Odds of FWS were lower among participants who were not self-quarantining compared to those self-quarantining all the time (OR: 0.32; 95% CI: 0.17 - 0.62). Furthermore, individuals with lower levels of concern about COVID-19 had lower odds of FWS than those extremely concerned. CONCLUSIONS: Household size, self-quarantine status, and concern about COVID-19 were significantly associated with FWS. These findings highlight the need to address the concerns of marginalized individuals to promote healthy behaviors.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".