Being fun: An overlooked indicator of childhood social status
Bibliographic record
Abstract
OBJECTIVE: The present study concerns an overlooked trait indicator of childhood peer status: Being fun. The study is designed to identify the degree to which being fun is uniquely associated with the peer status variables of likeability and popularity. METHOD: Two studies of children in grades 4 to 6 (ages 9 to 12) are reported. The first involved 306 girls and 305 boys attending school in northern Colombia. The second involved 363 girls and 299 boys attending school in southern Florida. Students completed similar peer nomination inventories, once in the first study and twice (8 weeks apart) in the second. RESULTS: In both studies, being fun was positively correlated with likeability and popularity. In the second study, being fun predicted subsequent changes in likeability and popularity, after controlling for factors known to be related to each. Initial likeability and popularity also predicted subsequent changes in perceptions of being fun. CONCLUSIONS: Anecdotal evidence suggests that children are intensely focused on having fun. The findings indicate that this focus extends beyond the immediate rewards that fun experiences provide; some portion of peer status is uniquely derived from the perception that one is fun to be around.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".