Correlations between foregrounding, reading strategy and theory of mind
Bibliographic record
Abstract
A number of studies have recently been produced in the U.S. and Canada linking theory of mind (the ability to accurately assess the mental states of other people) to lifetime exposure to literary, especially stylistically foregrounded, fiction. The paper presents an experiment devised to partially replicate and further develop this strand of research outside the English-speaking world. Subjects (Norwegian teacher training undergraduates) were asked to read a short story while assessing their reading experience on a number of variables. They were also tested for general reading skills and, in two different sessions, for their theory of mind abilities. In addition, they provided personal background information concerning their reading behavior and attitudes to literature. One group of subjects read the original story, which was rich in foregrounding, while another group read a manipulated, subliterary version of the story where foregrounding was minimized. The foregrounded version was expected to correlate with a broader range of affective responses and increased scores on theory of mind. The paper offers a first analysis of the data with regard to these hypotheses.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".