Kidh Fabric: Product Development for Community Business Reinforcement
Bibliographic record
Abstract
This research, Kidh fabric: product development for community business reinforcement was conducted with three main aims: 1) to study Kidh fabric history in northeastern Thailand; 2) to study problems and solutions related to processed fabric products; and 3) to study fabric product pattern design development for community business reinforcement. This qualitative study used a purposive random sampling technique, with samples including people involved with Tai Dam fabric products. Data were collected through structured interview, observation, focus group discussion and work shop.In addition, data reliability and validation tests were conducted with a triangulation method. The results show that Kidh Fabric production processes from three community business groups had the same points in keeping their unique designs and purposes to improve their own business and marketing. There needs to be coordination between community members in the production and design processes, as well as to increase product value by using new knowledge and technology. In conclusion, to develop Kidh fabric products for community reinforcement, all three communities need more support and cooperation from government units, private organization and community leaders. Moreover, these communities businesses need more knowledge and technological support to improve their production process, marketing, personalities in order to transform their community production units into strong and stable business groups.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".