Regulation of food supplements in Algeria: Current situation, issues, and perspectives
Bibliographic record
Abstract
Background: The Algerian food supplements market has witnessed substantial growth, especially during the COVID-19 pandemic. To safeguard consumer health, a robust regulatory framework for these products is imperative. Aims: This article thoroughly examines the existing regulatory framework for food supplements in Algeria, identifying shortcomings and potential areas for improvement. Methods: Regulatory texts published in the Algerian Official Journal were collected and analyzed. These texts were then compared with regulations from the USA, Australia, Canada, the European Union, and the Democratic Republic of Congo. Key regulatory aspects, including approval processes, manufacturing standards, adverse event reporting, labeling requirements, and evidentiary standards for claims, were scrutinized. Results: In Algeria, food supplements are classified as food products, mandating adherence to Good Hygiene Practices and Hazard Analysis and Critical Control Points (HACCP) guidelines. While labeling must avoid misleading claims, prior authorization for production and marketing is not required. Instead, compliance is ensured through batch analyses and market inspections conducted by the Ministry of Trade. A rapid alert system is in place to monitor supplements posing health risks. Conclusion: A comparison of the Algerian regulatory framework for food supplements with international standards reveals the need for significant improvement to enhance consumer protection. A revised version of this framework, initiated by an interministerial committee but yet to be published in the official journal, is expected to address and rectify these deficiencies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".