‘To prevent this disease, we have to stay at home, but if we stay at home, we die of hunger’ – Livelihoods, vulnerability and coping with Covid-19 in rural Mozambique
Bibliographic record
Abstract
Non-pharmaceutical interventions (NPIs) such as social distancing and travel restrictions have been introduced to prevent the spread of the novel coronavirus (hereinafter Covid). In many countries of the Global South, NPIs are affecting rural livelihoods, but in-depth empirical data on these impacts are limited. We traced the differentiated impacts of Covid NPIs throughout the start of the pandemic May to July 2020. We conducted qualitative weekly phone interviews (n = 441) with 92 panelists from nine contrasting rural communities across Mozambique (3–7 study weeks), exploring how panelists’ livelihoods changed and how the NPIs intersected with existing vulnerabilities, and created new exposures. The NPIs significantly re-shaped many livelihoods and placed greatest burdens on those with precarious incomes, women, children and the elderly, exacerbating existing vulnerabilities. Transport and trading restrictions and rising prices for consumables including food meant some respondents were concerned about dying not of Covid, but of hunger because of the disruptions caused by NPIs. No direct health impacts of the pandemic were reported in these communities during our interview period. Most market-orientated income diversification strategies largely failed to provide resilience to the NPI shocks. The exception was one specific case linked to a socially-minded value chain for baobab, where a strong duty of care helped avoid the collapse of incomes seen elsewhere. In contrast, agricultural and charcoal value chains either collapsed or saw producer prices and volumes reduced. The hyper-covariate, unprecedented nature of the shock caused significant restrictions on livelihoods through trading and transport limits and thus a region-wide decline in cash generation opportunities, which was seen as being unlike any prior shock. The scale of human-made interventions and their repercussions thus raises questions about the roles of institutional actors, diversification and socially-minded trading partners in addressing coping and vulnerability both conceptually and in policy-making.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".