Assessment of consumer demographics and food safety risks associated with ready-to-eat (RTE) homemade foods purchased online in the UAE
Bibliographic record
Abstract
In the UAE, female entrepreneurs, termed "Tajrat", sell a variety of homemade food products over online social media (OSM) platforms. Some of these food products are prepared and sold outside regulatory channels, with serious public health consequences. The study aimed to identify consumer demographics associated with purchasing of RTE, homemade food sold over in OSM platforms in the UAE and to assess the food quality by evaluating microbiological quality and fat percentage in RTE foods. A representative survey of the population of the UAE (n = 1303) was conducted, covering consumer demographics, frequency of purchase, and respondents' perception towards safety and nutritional value. 66 % of respondents were Emiratis, fifty percent of whom purchased RTE foods online. Moreover, 61 % of participants purchased from "Tajrat" via OSM as opposed to other sources. Convenience (47 %) and taste (41 %) were the main drivers for purchasing RTE homemade foods. Although 76 % of respondents have at least one member of their family considered vulnerable, the safety levels, quality, and nutritional value of such products did not carry the same significance. Microbiological analysis of 35 food samples purchased online from "Tajrat" was conducted. Listeria spp. was isolated from 22 % of the samples, 43 % showed positive Staphylococcus aureus , and 31 % of the samples had coliform bacteria. Total Fat Content of RTE homemade food samples ranged between 2.6 and 30 g/100 g which is considered high and can cause serious health issues if consumed frequently. Recommendations from this study will help policy makers and regulators in the UAE to develop and implement education strategies targeting homemade food handlers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".