Consumer attitudes towards healthy and organic food in the Kurdistan region of Iraq
Bibliographic record
Abstract
There has been increasing awareness of the benefits of healthy and organic food products as more knowledge has been gained on their effects on health, environment, social convenience and sustainable development. Acquiring insight into consumer attitudes is essential for the industry to grow. Compared with the rest of the world, the Kurdistan region of Iraq is still in the early stages of understanding the importance of healthy and organic food products. The study aim was to investigate the attitudes of Kurdish consumers concerning healthy and organic food. I administered an online survey to 452 respondents, and their responses were analysed by using descriptive statistics and performing correlation, linear regression and factor analysis. The findings indicated that health concerns were the main reason for healthy and organic food consumption. I also found that quality and taste were important factors in purchasing decisions and that consumers were willing to pay a premium price if these foods were available. However, there was a general lack of concern about food production effects on the environment and animal welfare. This research provides a new insight into the attitudes of Kurdish consumers in Iraq towards healthy and organic food. This population has not been covered before, which in turn will add to the literature on this subject.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".