The Perception of Virtual Residential Spaces
Bibliographic record
Abstract
This experiment examined how “warm” and “cool” video walkthroughs stimulated narratives. “Warm spaces” had red color schemes, whereas “cool” spaces were sparse with blue color schemes. In Part 1, 48 participants rated four “warm” and four “cool” walkthroughs on scales related to essential qualities of a home. “Warm” walkthroughs were more familiar, relaxing, and evoked more episodic memories compared with “cool” spaces. In Part 2, participants wrote story outlines set in two “warm” and two “cool” walkthroughs from “first” (Self) or “third-person” (Other) perspectives and rated their story-writing experiences. It was easier to write stories and more episodic memories were evoked in the Self condition. Stories were seen as less resolved when written from the Self perspective and set in “warm” spaces. The story outlines were qualitatively analyzed and frequency of the categories was determined. The evocative qualities and episodic memories evoked by the spaces were projected into the narratives.
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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 | 0.007 |
| 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 | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".