Utilizing Q-Methodology for the Study of the Behavior of the Audience of Creativity
Bibliographic record
Abstract
The study of Creativity from the standpoint of the Audience (e.g., any person that assesses a product as creative) has not been addressed yet from a naturalistic perspective in terms of the reactions of the individual according to the cultural group he/she belongs to. In this paper, a cultural group is defined as a group of individuals that have similar reactions to a stimulus (i.e., considering architectural objects as more creative than other objects). The present study presents a way to study Creativity from an interbehavioral standpoint by utilizing Q Methodology to capture the interaction between the Audience and the object. Thirty Participants (15 females and 15 males) from different occupations (art, science and various trades) were asked to organize sixty pictures (architecture, photography and furniture) in a Q-sort in terms of how creative they considered the picture was with respect to the others. The responses were grouped by three factors: photography preference, furniture preference and preference for architectural products. The results showed that the responses of the participants grouped them independently of their occupation or gender; showing specific tendencies on which objects they valued as most creative. Results are discussed in terms of how the factors represent the different cultural groups present in the participants’ sample, and their relation with previous research on the behavior of the Audience. The present results show promise of the use of the Q Methodology in the research of the behavior of the Audience from a naturalistic perspective.
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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 | 0.025 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".