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Record W6997234625

Understanding how to increase women’s acceptance and access to palm weevil larvae in peri-urban communities in the Ashanti region in Ghana

2023· dissertation· en· W6997234625 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2023
Typedissertation
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsMcGill University
Fundersnot available
KeywordsPalmWeevilLarvaPopulationAgriculture
DOInot available

Abstract

fetched live from OpenAlex

In low-and middle-income countries like Ghana, women are disproportionately affected by iron-deficiency anemia.Various strategies can effectively reduce iron-deficiency anemia at the population level, including food fortification, supplementation, and dietary improvement.Unfortunately, due to cultural, economic, and resource-related challenges, those have failed to reach Ghanaian women adequately and equitably, resulting in many not meeting their nutritional needs.There is a growing consensus that edible insects could serve as a complementary nutrition-sensitive strategy to alleviate nutritional deficiencies in low-and-middle-income countries.No study has yet examined the factors influencing the feasibility of this strategy for women in Ghana.The first study was formative research providing a general understanding of Ghanaians' perceptions on the consumption of palm weevil larvae.For the aforementioned strategy to be effective, women need to be willing to consume palm weevil larvae and feed it to their families.Mind mapping and focus group discussions were conducted on 121 Ghanaian women in five peri-urban communities in the Ashanti region and sought insight on the facilitators of palm weevil larvae's consumption, its socio-cultural and economic barriers, as well as women's general knowledge of iron-rich foods and anemia.An inductive thematic analysis of the focus group discussions and mind maps showed that women were generally motivated to consume palm weevil larvae for its nutritional and health benefits.Scarcity, difficult access and disgust, however, were the major barriers to the consumption of palm weevil larvae.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.096
GPT teacher head0.298
Teacher spread0.201 · 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.

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
Published2023
Admission routes1
Has abstractyes

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