Bibliographic record
Abstract
Dirty bread factories, the use of halal logo on food produced from unslaughtered chicken and other animals and having pig's DNA in food products as additives are major increasing concerns with rising mobility and awareness in Bingöl city East of Turkey.Religious beliefs influence the purchasers' behaviors and pigs, alcohol and foods dangerous for human body accepted as Najis (ritually unclean) are forbidden in Muslim religion.Hence, a survey with 500 respondents were carried out at Bingöl city at second quarter of 2016 to learn the awareness of inhabitants and compare its results with past studies done in Erbil city/Iraq Kurdistan and Yozgat/Turkey.Bingöl city people are known with their more conservative Islamic living styles in Turkey.Descriptive statistics like means, reliability analysis, factor analysis, one way One-Way ANOVA and correlation models are used to analyze data.Results have some familiarities and differences with Yozgat and Erbil cities results.The results can be used for further studies and commercial firms selling halal products at city.Taste, quality & organic group with 3.75 mean has the highest mean and other critical means come from certification and packaging groups.Moreover, Halal food label on packaging and certifications groups have positive correlation on buying behaviors of costumers.Low level awareness at city can be increased with seminars and classes as since just about 50% of them eat halal foods always.More controls over foods at local markets and groceries can be carried out to increase trust level of costumers as they do not wholly trust products at markets.Hence, they prefer to consume more locally produced organic foods if they can find with suitable prices.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".