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Record W2995142443 · doi:10.9734/ejnfs/2015/21265

Role of Effective Enforcement of Salt Iodization Legislation in Improving the Supply and Distribution of Adequately Iodized Salt

2015· article· en· W2995142443 on OpenAlexaff
Abdoualye Ndiaye Ndiaye, Banda Ndiaye, Venkatesh Mannar

Bibliographic record

VenueEuropean Journal of Nutrition & Food Safety · 2015
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsNutrition International
Fundersnot available
KeywordsLegislationIodised saltEnforcementDistribution (mathematics)BusinessEnvironmental healthMedicinePolitical scienceInternal medicineLawMathematics

Abstract

fetched live from OpenAlex

The production and distribution of non iodized salt is banned by the legislation in Senegal and the Ministry of Trade (MoT) supported by the police forces and the Department of Hygiene of the Ministry of Health is mandated to enforce this legislation. However, household use of iodized salt remains <70%. We undertook this survey to compare apparent governmental commitment to enforcing salt iodization legislation and production of iodized salt. Methods: Technical and logistical support were provided to regional offices of MoT covering salt producing regions and Five year data trends were collected from regional MoT offices in two salt producing regions. Analyses included: number and frequency of enforcement activities in productions sites, fines paid by defaulters and total production of adequately iodized salt in comparison to changes in leadership at these offices. Results: Between 2008 and 2012, the level of enforcement/ field controls decreased sharply in region 1 (from 138 to 35) and increased in region2 (from 30 to 140). Fines paid by defaulters between 2008 and 2012 were 600,000FCFA in region1 against 4,075,000FCFA in region2. In region 1, the production and distribution of adequately iodized salt declined from 20,000 to 12,000 MT per year in 2008 and2012, while in region2it steady increased from 6,000 to 25,000 MT per year in2008 and 2012, respectively. Conclusions: Whatever the resources used in training small salt producers, and communicating

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)0.001
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 score0.672
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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
Published2015
Admission routes1
Has abstractyes

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