“We are adapting to it because it is within us”: The co‐becoming of COVID‐19 in Malawi
Bibliographic record
Abstract
Abstract Using a case study design, this research explores the Coronavirus 2019 disease (COVID‐19) pandemic from the perspectives and worldviews of Malawians (Black/African knowledge) through the Bawaka Yolŋu ontology of co‐becoming (Black/Indigenous knowledge). This study seeks to examine the ways in which COVID‐19 has influenced perceptions of place and the places themselves, thereby contributing to the development of policies and strategies for effectively navigating and living with the ongoing COVID‐19 pandemic. The study involved forty‐one in‐depth semi‐structured interviews and two unstructured interviews, enabling a nuanced exploration of COVID‐19's impact through the diverse perspectives of Malawian knowledge holders including religious leaders, health‐care workers, farmers, and community leaders. The findings reveal a multifaceted transformation in the relationship of Malawians with nature, place, and one another. Nature, once a source of sustenance, has become a realm of danger due to its association with airborne transmission. Place, typically a communal space, has shifted towards individualized safety, necessitating changes in how homes are adapted and perceived. The communal fabric of Malawian society, deeply ingrained in communal practices, has been strained, altering traditional gatherings and societal interactions. This research adds depth to our understanding of COVID‐19's complex impacts, emphasizing the importance of cultural and environmental contexts in shaping responses to the pandemic. The insights gained hold significance for tailored policy interventions and community‐focused strategies to navigate and adapt to the evolving challenges presented by COVID‐19.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".