Perceived Innovativeness and Privacy Risk of Smart Toys in Brazil and Argentina
Bibliographic record
Abstract
A smart toy, such as "Hello Barbie," is a device consisting of a physical toy component that connects to a computing system with online services through networking to enhance the functionality of a traditional toy. Whilst these are new educational and entertaining values of smart toys, experts in western countries such as U.S. and Germany have warned consumers of the data security and privacy issues of these toys. In this preliminary research study, we particularly studied Brazilian and Argentinian consumers’ perceived innovativeness, risks and benefits of smart toys and their purchase intention toward such toys. Results indicate that Brazilian consumers have better perception and evaluation of the toy and thus higher purchase intention than Argentinian consumers do. Such difference may be explained by the cultural differences be-tween the two countries, such as relatively low vs. high uncertainty avoidance.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".