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Record W1970470173 · doi:10.5539/sar.v3n3p56

The Extent of Heat on Health and Sustainable Farming in Ghana –Bawku East

2014· article· en· W1970470173 on OpenAlexvenueno aff
Kwasi Frimpong, Jacque Oosthuizen, Eddie van Etten

Bibliographic record

VenueSustainable Agriculture Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsWet-bulb globe temperatureRest (music)ProductivityAgricultureTropicsWork (physics)GeographySocioeconomicsEnvironmental scienceMedicineAir temperatureMeteorologyBiologyEconomic growthEconomicsEcology

Abstract

fetched live from OpenAlex

<p>Little is known about the health effects of heat in outdoor work and appropriate work and rest schedules for farmers working in developing countries. As temperatures continue to increase in tropical regions, such as Northern Ghana, it is necessary to evaluate how farmers experience and respond to high heat exposures. In this study, WBGT (Wet Bulb Globe Temperature) estimates and the ISO work / rest standards were applied to a cohort of farmers in the rural areas of Bawku East, Northern Ghana, to assess how farmers respond to high heat and how much they rest to protect their health, as well as the level of heat on their productivity. WBGT data was recorded over a period of 6 months among vegetable, cereals, and legume farmers. The ISO proposed and actual rest regimes observed by farmers in the same time period were evaluated. In the dry season the dry bulb temperature rose as high as 45 ºC, while during the humid months of March and April WBGT rose to levels as high as 34 ºC. Farmers worked for nine hours a day during these hot periods with insufficient rest, which has adverse consequences on their health and productivity.</p>

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.349
Teacher spread0.306 · 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 designNot applicable
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

Citations6
Published2014
Admission routes1
Has abstractyes

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