Integrated developmental and green social work field education to control fall armyworm Infestation in maize crops in Malawi
Bibliographic record
Abstract
In Malawi, fall armyworm (FAW) infestation in maize crops is a problem of public importance as it reduces maize yields and exacerbates household food insecurity. In addition to pest resistance, the use of synthetic pesticides to control FAW negatively affects the health of farmers and the environment. Biochemical pesticides from plants contain naturally non-toxic chemotypes and are effective in controlling pests. Tephrosia vogelii plants contain these bioactive phytocompounds that have pesticidal properties. Geographical location and plant species influence the occurrence of phytocompounds in Tephrosia vogelii. Farmers in Sub Sahara-Africa are using Tephrosia vogelii as a pesticide but there are mixed research findings regarding its effectiveness in controlling FAW pests. This study was informed by developmental and Green Social Work frameworks to compare the effectiveness of Tephrosia vogelii leaves extracts, Belt 480 SC, and soap solution in controlling FAW in maize gardens. The study employed a randomized complete block design with four replication gardens and was conducted from November 2022 to March 2023. A social work field education student was assigned to coordinate the project. The study affirmed that the sampled Tephrosia vogelii leaf extracts contained pesticidal chemotypes. The results of field gardens suggest that Tephrosia vogelii leaf extracts have similar potency to Belt SC 480 chemical pesticide. It has been identified that Boom detergent soap is not as effective as Tephrosia vogelii leaf extracts. The study has social work field education implications for empowering practicum students to gain community mobilization skillsets, to participate in environmental justice advocacy, and to uphold social work values.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".