Clothing Design Preference of Silver Generation Women -Focus on Age 60 and More-
Bibliographic record
Abstract
This study was conducted for silver generation women, age 60 and more. Questionnaire was answered by the total 291 of women. Frequency analysis, t-test, ANOVA and Duncon-Test have been completed by using SPSS 12.0 tool. The conclusion of the study is below. First, silver generation women live in Seoul and South Gyeongsang Province. The data shows huge academic background gab among regions. Second, the following is the preferences found by 15 stimulants which expert groups identified based on demography. People in South Gyeongsang Province like default, tailored, three-button jacket more. People in South Gyeongsang Province prefer to Chanel jackets and people in their 70s prefer to it than in 60s, stand collar casual jacket for color and material, and the less they are educated, the more they like the jackets. And those who have less personal expenses tend to prefer to it. South Gyeongsang Province shows preference for semi polo-neck sweater. Highly educated did not show any preference for it. Women in their 70s tend to like blouses with round neckline. The data shows there is significant difference of preference for design, color and material for coloration vest between education levels. The less educated tends to like it. People in South Gyeongsang Province and those who live with their children are in favor with half sleeve jackets for colors and materials. All in Seoul and South Gyeongsang Province do not like three-quarter-length sleeve jackets because those jacket have wide and deep plunging neckline. The study showed people living in Seoul, in their 60s, highly-educated tend to favor polo shirts significantly. Seoul favor basic straight pants and people with any level of education excluding elementary prefer to it. The highly-educated and those who have a bigger allowance tend not to prefer to baggy trousers. In conclusion, Fifteen incentives (clothing design) for semi polo-neck sweaters, polo t-shirts, basic straight pants are more proper to silver generation women in their 60s, living in Seoul. Other designs are desirably applicable to customers on a national scale at middle prices.
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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 | 0.000 | 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 | 0.000 | 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) | 0.004 | 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 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".