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Record W4378214257 · doi:10.32920/23159867.v1

Creators as Operators: an Examination of the Effects of the COPPA Rule Application on the YouTube Kid’s Content Ecosystem

2023· preprint· en· W4378214257 on OpenAlexaff
Fabiana Pestana Barbosa

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPopularityStatus quoInternet privacyHarmRevenueInfographicCommunication sourcePsychologyAdvertisingPolitical scienceBusinessComputer scienceSocial psychologyLaw

Abstract

fetched live from OpenAlex

<p>YouTube is a video-sharing website and application consisting of user-generated content (UGC), formally restricted to people 13 and older. However, its popularity with a younger audience has been knowingly growing, and in September 2019, the Federal Trade Commission (FTC) claimed that YouTube illegally collected personal information from children without their parents' consent, violating the Children's Online Privacy Protection Act (COPPA). To settle the allegations, Google and YouTube were required to pay a $170 million fine and implement a system to obligate channel owners to identify if their content is child-directed. </p> <p>This study is comprised of an extensive literature review and a detailed content analysis of comments, videos, official communications, and documents related to the settlement, aiming to identify the potential impacts on the various actors and uncover opportunities to improve this policy implementation in the future. The results demonstrate that both creators and parents expect that children's content creators will suffer a significant reduction in their ability to generate revenue and, consequently, be discouraged from starting or continuing to create children content, either abandoning their channels or switching their content strategies toward an older audience. The results also indicate that female creators are at higher risk of being affected. </p> <p>Overall, these findings support the notion that the COPPA rule’s implementation will harm children's content creators' abilities to build a career, contributing to the return of the <em>status quo ante</em>, where big companies dominate children content's production, and will also potentialize gender inequality on media. Furthermore, by reducing the availability of appropriate content on YouTube, it will undermine parents' ability to make choices, and their children will either lose access to online content or be exposed to more mature videos and ads. Thus, there is a need to find a balance between protecting children's online privacy and preserving the platforms' sustainability, to contribute to the universal access to diverse and high-quality digital resources for children. </p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.279
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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