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Record W3201061471 · doi:10.1177/11786302211043033

Agrochemicals Use Practices and Health Challenges of Smallholder Farmers in Ghana

2021· article· en· W3201061471 on OpenAlexafffund
Suleyman M. Demi, Suzanne R. Sicchia

Bibliographic record

VenueEnvironmental Health Insights · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersUniversity of Toronto
KeywordsAgrochemicalNonprobability samplingAgricultureBusinessGovernment (linguistics)Focus groupEnvironmental healthQualitative propertySimple random sampleEnvironmental planningGeographyMarketingMedicinePopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Globally, Africa is one of the continents that uses the lowest quantity of agrochemicals in farming. However, unsafe chemical use practices are high among farmers in Africa, posing serious health and environmental consequences. This study seeks to address three questions: (1) What factors motivate/compel smallholder farmers in Ghana to use agrochemicals? (2) What safety precautions or unsafe chemical use practices can be found in the communities? (3) What are the health implications of agrochemical use among smallholder farmers in Ghana? METHODOLOGY: The study used purposive and simple random sampling techniques to select 136 individuals for the survey, out of which 31 individuals were eliminated, and 105 participants were selected for in-depth interviews and focus group discussions. Additionally, participants' observations were collected, workshops were facilitated, and documents analyses were conducted. Qualitative data were analyzed using NVivo software and the quantitative data were analyzed using SPSS version 23.0. FINDINGS: The study found that environmental challenges, activities of NGOs, government policy, lack of or high cost of labor, and competition among farmers were major factors influencing farmers' decisions to use agrochemicals. Present agrochemical use in Ghana poses a risk to health and the environment. Finally, the study discovered chemical poisoning and low self-reported health quality as major health implications of agrochemical use in the communities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.093
GPT teacher head0.290
Teacher spread0.197 · 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

Citations46
Published2021
Admission routes2
Has abstractyes

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