Nostalgia as inspiration for fashion design – Designing the present of future through nostalgia
Bibliographic record
Abstract
Nostalgia is a recurring theme throughout the creative process of many fashion designers (Mollow, 2004). According to Tilburg, Sedikides & Wildschut (2015), nostalgia can particularly favour and encourage creativity. Thanks to their research on creativity and literature, based on a nostalgic daydream of the present and the future, they have come to the conclusion thatnostalgia can be a very efficient tool to spur on a creative process. But how does nostalgia fuel a creative approach in fashion design? How does the past merge with the present to formulate fashion’s future? This phenomenon will be explored by using nostalgia as a startingpoint for the creative process of three designers, as well as for threeof the author’s creative projects in fashion design: the 3D Tutu, the 3D dress and the mathDress. This research aims to concretely demonstrate how nostalgia can be applied in the conception of a garment collection for fashion design students or professionals, and how to gain a deeper insight on this emotion without losing one’s self in it, or feeling overwhelmed.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.039 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".