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Record W2123181240 · doi:10.5539/jps.v1n2p114

Urban Vegetable Farmworkers Beliefs and Perception of Risks Associated with Pesticides Exposure: A Case of Gaborone City, Botswana

2012· article· en· W2123181240 on OpenAlexvenueno aff
Gobusamng Leungo, Motshwari Obopile, Otsoseng Oagile, Mogapi E. Madisa, Yoseph Assefa

Bibliographic record

VenueJournal of Plant Studies · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsPesticideEnvironmental healthHarmInterviewRisk perceptionHazardous wasteOccupational safety and healthBusinessSocioeconomicsGeographyPerceptionMedicinePsychologyEngineeringPolitical scienceSociology

Abstract

fetched live from OpenAlex

A survey was conducted in urban horticultural setting in Gaborone City, Botswana from 4th to 31st March 2010 by interviewing 56 farmworkers on their perception and knowledge of risks and hazards associated with exposure to pesticides. The study showed that most farmers relied heavily on pesticides and applied them without considering economic damage to crop. Most pesticides used are classified as extremely hazardous by the World Health Organisatopn (WHO). Majority of farmworkers were aware of health risks and environmental contamination associated with pesticides. The awareness of pesticide harm was significantly influenced by educational background, training on pesticide use and experience on vegetable production. While the percentage of educated and experienced workers was higher (> 50%), training from extension services was only 14% indicating the need for more training to maintain the awareness standard. The study needs to be done in other urban centres of Botswana to get countrywide information on farmworkers awareness of pesticide harm.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.282
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Plant StudiesSame topicPesticide Exposure and ToxicityFrench-language works237,207