Bibliographic record
Abstract
With the help of fashion and apparel industry/business, the economy of Gifu area had been developed after the World War II. But after the collapse of the bubble economy, economical and social circumstances have been changing drastically. This change also influenced the vitalities of apparel industry/business and city center of Gifu area. This paper discusses how the view of citizens reflects the reform of administration, industry and urban development, through the questionnaire survey of female of wide range of age, in comparison with the result of survey of students five years ago. We gathered information by the method from 258 female, from the ages of 16 to 60. By using SD method and factor analysis, we investigate (1) the actual condition of the fashion life, (2) interest about fashion information, (3) image about fashion sense of Gifu area and (4) image about fashion/apparel industry/business of Gifu area. The results are as follows: (1) It is increasing as compared with five years ago that the rate of person who goes to Nagoya when she buys her clothes to the satisfaction of her fashion sense. (2) They mainly get fashion information from magazine, while inter-net is not so common to get it. (3) The results of factor analysis show that fashion sense of Gifu area is not so attractive for female. (4) It is not changed from five years ago that little recognition of Gifu as the area of fashion/apparel industry/business and negative image against station front area. But they feel new waves as to the activities of "Active G" and "Fashion Library".
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".