PARENTS’ ATTITUDE TO TOYS CONNECTED TO THE INTERNET
Bibliographic record
Abstract
children. These include toys connected to the internet called IoToys (Internet of Toys). It is critical to understand how children interact with digital toys, and to assess the risks and opportunities they bring to children's development. This report focuses on some preliminary results of the research project “Toys connected to the Internet: studying the risks and opportunities for child development", conducted by the Center for Interdisciplinary Research on Contemporary Childhood of MSUPE in 2021-2022. The task of the first stage of the study was to analyze the position of parents in relation to IoToys. The research group analyzed 300 reviews of parents who bought their children a toy connected to the internet (Smart Bear) on the sites of online stores. The data testified that, despite product recommendations, parents tended to buy the toy for children of younger ages. As positive characteristics, most parents identified the external signs of the toy (image, voice), rather than its digital characteristics. Of all the functions presented, entertainment content (listening to fairy tales, songs) and reminders were mainly used. The least popular was educational content. Half of the parents who spoke about the child's attitude toward the toy noted that the child perceived it as a friend. At the same time, a quarter reported that the child was afraid of the toy because it behaves like a living creature. The obtained data revealed parents’ insufficient awareness about the internet toy , its functions, possibilities, and risks of use. Further research is needed to determine the role of the adult as a facilitator when playing with a digital toy
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".