Ensuring Public Health: Monitoring of Hormone Residues in Poultry Meat
Bibliographic record
Abstract
The study's main purpose of addressing the problem of hormone content in poultry meat is to analyze the literature and such an official approach as state monitoring for 2017-2020. Research has shown that hormones have not been used in poultry farming for more than 50 years in the EU, the USA, Canada and other countries. In addition, there are strict international laws, including in Ukraine, on the control of the use of hormones in poultry to ensure public health. The urgency of solving the scientific problem is that despite the above, in the literature for the last decades there are reports based on consumer surveys (from 40 to 60%) on the negative impact of poultry meat on the content of hormones on their health. This negatively affects the consumption and image of poultry producers. Such trends are observed, including in Ukraine. This encourages the provision of scientifically sound information on this issue. The study of the content of hormones in poultry meat in the article is carried out in the following logical sequence: the analysis of international scientific literature on the content of hormones in poultry meat, as well as data from the State Statistics Service of Ukraine on the trend of poultry consumption and increased demand among consumers for this type of meat. In addition, the article analyzes the official data of state monitoring of residual hormones in poultry meat. The following methods became the methodological tools of the conducted research: analysis of literature sources for 10 years, the period of research of the state monitoring is chosen 2017-2020. The object of the study was the biased attitude of some consumers to the safety of poultry meat in terms of hormones, which arose as a result of the spread of the myth of the use of hormones in poultry. The subject of the research was the analysis of current literature data and the results of official national monitoring of the content of hormones in poultry meat. Research shows that as a result of constant strict official controls on the use of hormones in poultry and the inefficiency of their use for poultry producers, the latter amount of hormones is at a minimum physiological level that does not harm public health. Our state monitoring studies show proper state control and provide guarantees to consumers in the consumption of safe poultry meat. The results of this study can be useful for consumers, scientists, and students in the field of food safety and our country as a whole to disseminate scientifically sound information in the field of state control over food safety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".