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Record W2266242491

Pesticide safety practice and its determinants among small scale vegetables farmers in Eyasi area, Arusha region Tanzania

2015· article· en· W2266242491 on OpenAlexaboutno aff
Innocent Semali, Vera Ngowi, Mary Macha

Bibliographic record

VenueEast African Journal of Public Health · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsTanzaniaPesticideAgricultureEnvironmental healthMarital statusAgricultural scienceQuarter (Canadian coin)MedicineBusinessSocioeconomicsToxicologyGeographyPopulationEnvironmental planningEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Background: Strategies to achieve the millennium agricultural development goals include increased use of pesticides to increase agricultural production in poor countries. However, the increased availability and use of such chemicals need to be paralleled with national and personal level practices to maximize safety for communities and environment. Aim and methods: The aim of this study was to determine the pesticide safety practices among rural farmers in Karatu District in Northern Tanzania. Farmers practicing horticulture farming in Mang’ola Division were interviewed about their practices during and after pesticides application. Results: The study included 148 farmers of whom 79.7% were male. A significantly high proportion (77.7%) of the farmers did not use protective gear while applying pesticides. A notable percentage ate while applying pesticides (17.6%), one out of five took fluids and about a quarter smoked cigarettes. Factors found to be significantly associated with those practices were education, marital status, reporting frequent household spraying, long duration since starting to apply pesticides and farm size (p<0.05). Conclusions: Given the lack of protective behavior, it is then very important that farmers and farm workers are reminded of the hazardous nature of pesticides and the need to have their health monitored regularly. Special educational and information strategies have to focus on those with low education, who are unmarried, working on large farms and have a high frequency of applying pesticides. To enhance sustained education and supervisions, community level surveillance and supervisors could be introduced.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.271
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEast African Journal of Public HealthSame topicPesticide Exposure and ToxicityFrench-language works237,207