Up-Cycling Trend Analysis in Fashion Industries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Consumers around the world became aware that "the environmenta and climate chang" is one of the most important social issues through experiencing rapid climate shift. Consuming patterns have changed according to heightening of interest in the environment and over a quarter of consumers showed their purchasing preference for eco-friendly products even though they are more expensive. Consumers' eco-friend propensity has affected retailers and manufacturers. The purposes of this study were to identify the concept of fashion up-cycling and to analyze up-cycling fashion brands. The definition of up-cycling in fashion industries is to manufacture highly susceptible and high-valued fashion products with creative idea or design inspiration by using second hand resources. There are similar terms such as trashion(trash + fashion), redesign, and remanufacturing. Techniques for fashion up-cycling drawn from case analysis of fashion companies were redesigning old fashioned clothing in their storehouses, redesigning small pieces of textiles from sewing companies, and redesigning second hand clothing with creative ideas or inspiration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it