A Theoretical Framework for Organizing the Effect of the Internet on Cognitive Development
Bibliographic record
Abstract
Abstract: The number of children and adolescents accessing the Internet as well as the amount of time online are steadily increasing. The most common online activities include playing video games, navigating web sites, and communicating via chat rooms, email, and instant messaging. A theoretical framework for understanding the effects of Internet use on cognitive development is presented. The proposed framework, based on the cognitive information processing model, the sociocultural perspective, and the PASS cognitive processing model, organizes previous research in terms of the cognitive consequences of common online activities. From a cognitive-developmental perspective, the Internet is a cultural tool that influences cognitive processes and an environmental stimulus that contributes to the formation of specific cognitive architecture. Media is a contraction of the term media of communication, referring to organized dissemination of information and entertainment such as newspapers, magazines, film, radio, television, and the World Wide Web (McChesney, 2004). In a comprehensive survey of media use in preschool children, Rideout, Vandewater, and Wartella (2003) reported that 99 % live in a home with a television, half have more than two televisions in their home, and 36 % have a television in their bedroom. “Nearly half (48%) of all children six and under have used a computer, and more than one in four (30%) have played video games ” (p. 4). Given such early and extensive use, the impact of media on
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".