A Model Development of Thai Rice Label and Package for Heath Conscious Group of Consumers on Social Media
Bibliographic record
Abstract
<p>The objectives of this research were to explore Thai rice consumption behavior and to develop the rice package as perceived by health conscious group of consumers on social media. The research methodology adopted mixed methods by means of marketing survey research and using research results to develop the product and package prototypes. The samples were 71 online-based consumers. The research tool was a questionnaire on general status of respondents and factors of their rice purchasing. Descriptive analysis was for the data analysis. Results revealed that the marketing mix factors affecting the consumers‘ decision to purchase rice comprised the following aspects, 1) product: rice cultivating areas, health benefits, and package, respectively; 2) price: best suit to rice quality, clear price tag, and saving price, respectively; 3) distribution channels: clean distribution sites, convenient transport, and enough car parking spaces, respectively; 4) marketing promotion: sale, discount coupon, and point-of-purchase displays, respectively. These are key issues to be considered. Regarding the label and logo design, the design work needed to present complete and clear information referring to essential quality of the product, and represent distinction and uniqueness. Product design needed to consider how to facilitate convenient transport, convenient use by consumers, i.e. opening-reclosing the package, and strength and firmness to effectively support the product, respectively.</p>
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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".