Moving beyond “Spoon” tasks: When do children autocue their episodic future thought?
Bibliographic record
Abstract
Much developmental (and comparative) research has used Tulving's Spoon test (i.e., whether an individual will select an item needed to solve a future problem) as the basis for designing tasks to measure episodic future thinking, defined as the capacity to mentally pre-experience the future. There is, however, intense debate about whether these tasks successfully do so. Most notably, it has been argued that children may pass (i.e., select an item with future utility) by drawing on non-episodic, associative processes, rather than on the capacity to represent the future, per se. Although subsequent developmental tasks have sought to address this limitation, we highlight what we argue is a more fundamental shortcoming of Spoon tasks: they prompt future-directed action making it impossible to determine whether children have used their episodic future thinking to guide their behavior. Accordingly, we know little about children's thought about the future that is independently generated (i.e., without prompting), or autocued, and is subsequently reflected (and measurable) by children's actions. We argue that this capacity is a critical, and heretofore overlooked, transition in future-oriented cognition that may not occur until middle childhood. We further hypothesize that it is reliant on children developing richer and more detailed future event representations, along with the necessary cognitive control to transform these representations into actions that serve to benefit their future selves. The time is ripe for researchers to explore this aspect of cognitive development and we suggest several novel approaches to do so. This article is categorized under: Cognitive Biology > Cognitive Development.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".