Drawing Privacy: How Children Conceptualize Regulation and Content Across Development
Bibliographic record
Abstract
Children’s understanding of privacy develops as they navigate both physical and digital spaces. This study examines how children aged 3- to 13- years-old conceptualize privacy through their drawings, analyzing data from the Privacy Illustrated dataset. We explored two key dimensions: regulation (mechanisms controlling access, such as doors) and content (what children consider private, such as bedrooms or intellectual property). Our findings suggest that as children get older, they are more likely to view privacy as something that can be actively managed using physical barriers and control mechanisms. In contrast, younger children often depicted privacy as simply being alone. Content-related depictions remained relatively stable across ages, though older children included more abstract ideas, such as digital privacy. This study provides a novel framework for examining privacy development, highlighting distinct but interrelated dimensions of privacy.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".