Screen Time and Media Consumption: The Role of Technology in Childhood Development
Bibliographic record
Abstract
For the last century, technology has actively shaped the childhoods of many generations and has become a fundamental aspect of childhood. From the introduction of the radio and television in the 1900s to digital technology and gaming platforms in the 21st century, children have constantly been exposed to various forms of technology that have aided their understanding of the world. Technology use is not inherently harmful, as its establishment and progression have contributed to a comprehensive understanding of childhood. Notably, the introduction of the internet has enabled national and global access to information, allowing individuals to gain valuable knowledge related to children's development from educated professionals. Further, the interconnectedness of social media facilitates the exchange of information worldwide, expanding an individual’s perspective and understanding of childhood. However, the rapid advancement of technology from the early modern world to the contemporary digital world has perpetuated issues associated with the overreliance on digital devices. Children’s unrestricted access to technology, in conjunction with the intensification of media consumption and screen time, is particularly concerning for children’s cognitive development and social interactions. It has raised public health concerns, threatening the healthy and normal development of children.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".