Does reading about fictional minds make us more curious about real ones?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Although there is a large body of research assessing whether exposure to narratives boosts social cognition immediately afterward, not much research has investigated the underlying mechanism of this putative effect. This experiment investigates the possibility that reading a narrative increases social curiosity directly afterward, which might explain the short-term boosts in social cognition reported by some others. We developed a novel measure of state social curiosity and collected data from participants ( N = 222) who were randomly assigned to read an excerpt of narrative fiction or expository nonfiction. Contrary to our expectations, we found that those who read a narrative exhibited less social curiosity afterward than those who read an expository text. This result was not moderated by trait social curiosity. An exploratory analysis uncovered that the degree to which texts present readers with social targets predicted less social curiosity. Our experiment demonstrates that reading narratives, or possibly texts with social content in general, may engage and fatigue social-cognitive abilities, causing a temporary decrease in social curiosity. Such texts might also temporarily satisfy the need for social connection, temporarily reducing social curiosity. Both accounts are in line with theories describing how narratives result in better social cognition over the long term.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it