Do Massed Presentations Make People Like Paintings More Than Spaced Presentations?
Bibliographic record
Abstract
This study investigated how spacing and massing affected the extent to which the photographs of paintings are favoured. In this study, 50 individuals participated in one of two conditions. We used a survey to conduct this experiment. In the survey, images of paintings were displayed in groups of six on a web page. One massed set presented paintings by one artist. The other spaced set presented six images of paintings, each by a different artist, shown one directly after another. All sets of six images were featured on a single survey page. Based on many past studies, familiarity boosts preferences toward a certain object, in our case, paintings. When many paintings by the same artist are grouped together, familiarity encourages higher favourability ratings. The spacing effect, which delays exposure to consecutive objects, helps participants remember the paintings more, encouraging higher favourability scores at the last phase, when thumbprint galleries are shown, than at the initial rating. The study gathered inconclusive evidence about the impact of spacing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".