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Record W4403641483 · doi:10.52968/28469840

Responsible Stakeholders in Food Risks Communication and Informed Consumers in Surulere Area of Lagos State, Nigeria

2022· article· en· W4403641483 on OpenAlexaff

Bibliographic record

Venue˜The œNewsorbit · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsState (computer science)BusinessEnvironmental healthRisk communicationMedicineComputer science

Abstract

fetched live from OpenAlex

In developing countries, the capacity to handle life-threatening health and nutritional risks is under great threat. Studies have emphasised effective communication of food risks as a measure for motivating behavioural patterns which would correct this imbalance. This study investigates the media used for publicity of food risks, level of awareness and sensitivity of consumers, as well as stakeholders' collaboration for effective prevention and control of food risks. The mixed-method design utilised involved the distribution of 110 copies of questionnaires among consumers within Surulere Local Government in Lagos and interview sessions with representatives of food manufacturing companies, mass media and regulatory bodies. Television, radio, social media, and public messages by the National Agency for Food and Drug Administration and Control (NAFDAC) were prominent media of food risks communication; the activities of the regulators led to increase in consumers' awareness and sensitivity to food risks and their benefits. Manufacturers were found to adhere to standards in food production, storage, and distribution. There was an effective collaboration among stakeholders and leading to food safety, trust and standard maintenance, and quick information provisioning.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.164
GPT teacher head0.290
Teacher spread0.126 · 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
Published2022
Admission routes1
Has abstractyes

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