Are the classic false belief tasks cursed? Young children are just as likely as older children to pass a false belief task when they are not required to overcome the curse of knowledge
Bibliographic record
Abstract
The question of when children understand that others have minds that can represent or misrepresent reality (i.e., possess a 'Theory of Mind') is hotly debated. This understanding plays a fundamental role in social interaction (e.g., interpreting human behavior, communicating, empathizing). Most research on this topic has relied on false belief tasks such as the 'Sally-Anne Task', because researchers have argued that it is the strongest litmus test examining one's understanding that the mind can misrepresent reality. Unfortunately, in addition to a variety of other cognitive demands this widely used measure also unnecessarily involves overcoming a bias that is especially pronounced in young children-the 'curse of knowledge' (the tendency to be biased by one's knowledge when considering less-informed perspectives). Three- to 6-year-old's (n = 230) false belief reasoning was examined across tasks that either did, or did not, require overcoming the curse of knowledge, revealing that when the curse of knowledge was removed three-year-olds were significantly better at inferring false beliefs, and as accurate as five- and six-year-olds. These findings reveal that the classic task is not specifically measuring false belief understanding. Instead, previously observed developmental changes in children's performance could be attributed to the ability to overcome the curse of knowledge. Similarly, previously observed relationships between individual differences in false belief reasoning and a variety of social outcomes could instead be the result of individual differences in the ability to overcome the curse of knowledge, highlighting the need to re-evaluate how best to interpret large bodies of research on false belief reasoning and social-emotional functioning.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".