COVID-19 Pandemic, Economic Livelihoods, and the Division of Labor in Rural Communities of Delta and Edo States in Nigeria
Bibliographic record
Abstract
The COVID-19 pandemic affected economic, social, health, and political aspects of most global, national, and local populations, including urban and rural communities. Government measures like lockdowns resulted in the closure of schools and businesses, while social distancing preventing group gatherings impacted public and private spaces. Based on key informants’ interviews with 36 participants drawn equally from three senatorial districts of Edo and Delta states of Nigeria, we analyzed the impact of the COVID-19 pandemic on the type of work men and women do and division of household activities, such as cooking, child, and family care. The findings show that traditional gender role ideology (GRI) defines and shapes rural men’s and women’s work, with women more engaged in farming, rearing livestock, and trading while men are engaged in farming, rearing livestock, and carrying out skilled jobs like carpentry, plumbing, and blacksmithing. The lockdown of schools and workplaces resulted in women disproportionately bearing the burden of cooking and caring for children, the elderly, and the sick. A few rural men shared childcare, while women spent more time on housework and childcare activities than in the pre-pandemic period when children were in school for 6–7 h daily. During the pandemic, rural men and women spent more time with the children, such that rural women stayed at home or took children to the farms and marketplaces where possible. Older siblings and the elderly also provided support for women. In conclusion, work and family activities during COVID were, to an extent, difficult to manage as parents had to cope with increasing food insecurity, economic and transportation costs, and social deprivation fostered by social norms, values, and practices that perpetuate gender inequality and marginalization of women.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".