Preliminary evidence for progressions in ownership reasoning over the preschool period.
Bibliographic record
Abstract
= 4.50-5.00, living in Michigan in the United States. We use a battery of four established ownership tasks that tested different aspects of children's ownership thinking. A Guttman test revealed a reliable sequence that explained 81.9% of children's performance. Namely, we discovered that identifying familiar owned objects emerged first, control of permission as a cue to ownership second, understanding ownership transfers third, and the tracking of sets of identical objects last. This ordering suggests two foundational ownership abilities on which more complex reasoning may be built: the ability to include information about familiar owners in children's mental models of objects and recognizing that control is central to ownership. The observed progression is an important first step toward developing a formal ownership scale. This study paves the way for mapping the conceptual and information-processing demands (e.g., executive functioning, memory) that likely underlie change in ownership thinking across childhood. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".