The way we encounter reading material influences how frequently we mind wander
Bibliographic record
Abstract
We examined whether different encounters of reading material influence the likelihood of mind wandering, memory for the material, and the ratings of interest in the material. In a within-subjects design participants experienced three different reading encounters: (1) reading a passage aloud, (2) listening to a passage being read to them, and (3) reading a passage silently. Throughout each reading encounter probes were given in order to identify mind wandering. After finishing the passage participants also rated how interesting it was and completed a content recognition test. Results showed that reading aloud led to the least amount of mind wandering, while listening to the passage led to the most mind wandering. Listening to the passage was also associated with the poorest memory performance and the least interest in the material. Finally, within the silent reading and listening encounters we observed negative relations between mind wandering and both memory performance and interest in the material, replicating previous findings. Taken together, the present findings improve our understanding of the nature of mind wandering while reading, and have potentially important implications for readers seeking to take advantage of the convenience of audiobooks and podcasts.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".