Clothing Taskscape as an Approach Toward Assessment of User Needs
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
This study highlights use of the clothing taskscape (CT) to assess user needs, characterize design problems, and develop design criteria by considering relationships across people, their clothing, environments, activities, and tasks. Two case studies—a liquor store uniform and outdoor winter sporting clothing for seated clients—are used to illustrate how the CT may be operationalized. Data collection included observation and interviews to identify problems and determine design attributes needed in our respective clothing categories. Data were thematically analyzed. Findings in the uniform case study included problems related to uniform styling, fit, fabric, branding, and visual identity. Findings in the winter sporting clothing case study included procurement, garment styling, fit, branding, visual identity, storage of personal effects, storage of large-sized garments, and laundering practices. Use of the CT has the potential to guide designers toward more holistic assessment of the use scenario to assess user needs and develop design criteria.
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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 | 0.000 | 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 | 0.001 |
| 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 it