Verbal Explanations and Item Choices as Joint Indices of Children’s Episodic Foresight
Bibliographic record
Abstract
The ability to project oneself forward in time and imagine a future episode, known as episodic foresight (EpF), is an important aspect of future thinking. EpF tasks often involve children choosing an item for a future episode, yet the degree to which future projection is required to succeed – versus memory or semantic associations – has been debated. Using existing data (N = 158 3-to 5-year-olds) that included two popular measures of EpF (the “Spoon” and Picture-book tasks), we systematically examined the extent to which an ostensibly future-directed action (i.e., selecting the item with future utility) mapped onto future orientation, episodicity, and self-projection (assessed through pronoun use) in children’s verbal explanations. For each task, we examined the effect of item choice (i.e., whether the item selected could be utilized in the future scenario or not) and age on children’s verbal explanations. Results showed that children’s explanations were more future-oriented and included more personal pronouns on the Picture-book task compared to the Spoon task but did not differ in episodicity or frequency of impersonal pronoun use. Further, age and item choice were significant predictors of future orientation and episodicity in children’s Picture-book task explanations (but results varied by trial). On the Spoon task, age and item choice significantly predicted children’s future orientation, while item choice significantly predicted episodicity. Our study highlights the correspondence between Canadian children’s item choices and explanations, while also showing that verbal explanations provide unique insight into the processes involved in EpF (e.g., future orientation, episodic processes, and self-projection).
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".