Self-Esteem and Use of the Internet among Young School-Age Children
Bibliographic record
Abstract
The literature suggests a relationship between technology use and self-esteem. Such research has failed toconsider young school-aged children and their use of the internet, particularly across contexts. Thirty-eightchildren aged 6 to 8 years rated the level and nature of their internet use (email, instant message, play games,visit websites) at home, school and in the community (i.e., at someone else’s house). They also rated items thatmeasured home, school and peer self-esteem. Instant messaging at school explained 21% of the differences inschool self-esteem. As children tended to report instant messaging at school, they also tended to report thehighest school-based self-esteem. Instant messaging at someone else’s house explained 11% of the differences inhome self-esteem. As children tended to report instant messaging at someone else’s house, they also tended toreport the lowest home self-esteem. Visiting websites at someone else’s house explained 10% of the differencesin peer self-esteem. As children tended to report visiting websites at someone else’s house, they also tended toreport the highest peer self-esteem. Internet use during the early school years is related to children’s sense of selfand mediated by context.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".