Understanding Taiwanese female baby boomers through their perceptions of clothing and appearance
Bibliographic record
Abstract
The objectives of this study are twofold: (1) to provide insights and in-depth information regarding the impact of attitudes of female baby boomers in Taiwan toward aging through clothing, and (2) to understand how female baby boomers in Taiwan behave in different contexts in regard to clothing choice, usage and consumption. In order to understand how baby boomers think, feel and behave during the process of aging, clothing was selected as a vehicle to illuminate the complex relationships among various attributes—physiological and psychological change, dress and appearance, body image, lifestyle, and social activities. The qualitative research method was used to collect data from 14 mature female consumers ranging in age from 50 to 59 years. According to our findings, social activities and appropriate clothing styles can provide aging consumers self-assurance/-gratification as well as a healthy state of mind and spirit. It is evident that many Taiwanese baby boomers were concerned with modesty, age appropriateness, and physical and psychological comfort when it comes to apparel consumption. Although their bodies transformed with age, most of our informants expressed an acceptance and sense of comfort with their physical change, and they felt “young-at-heart”; therefore, chronological age is not a good indicator of consumer attitudes towards the evolving stages of life.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".