Trajectories of the Creative Process: A Multiple-Drafts Analysis of Graphic Design
Bibliographic record
Abstract
Most experimental analyses of creativity look at one-shot production tasks. However, real-world creativity occurs over long periods of time and involves extensive exploration and revision. We carried out a week-long study in which graphic design students created an advertisement for a fictional business, submitting daily drafts of their evolving ad. By analyzing the successive changes to these ads across the 7 daily drafts, we sought to characterize the trajectory of the creative process for each designer. In doing so, we elaborated on the core concept of the Geneplore model (i.e. generation + exploration) by proposing a 2 × 2 predictive scheme of creative trajectories in which a) the generative phase specifies either a global plan of the final product or merely a kernel idea for it, and b) the exploratory phase proceeds in either a linear or nonlinear manner, thereby resulting in four basic trajectories. We analyzed the relative frequency of these trajectory-types in our 37 graphic design students using a novel “change analysis” method. In addition, we examined how the novelty, quality, and stylistic features of the final ad related to the trajectory-type of the creator. The results revealed that there are multiple routes toward achieving a comparable level of novelty in a creative product.
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".