"Do as I say, not as I do": Family influences on children's safety and risk behaviors.
Bibliographic record
Abstract
OBJECTIVE: Although there is considerable speculation that family-based socialization processes influence children's safety and risk behaviors, few studies have addressed this important issue. The present study compared the impact of parent practices and teaching about safety on children's current behaviors and their intended future behaviors when they reach adulthood. DESIGN AND MEASURES: Children 7 to 12 years of age were interviewed and asked to report on their parents' practices and teachings (discussions, expectations for children's behavior) regarding five common safety behaviors. As well, the children reported on their own current practices and how they intended to behave when an adult. When appropriate, they provided explanations about why their parents engage in fewer safety behaviors than they required of their children. RESULTS: Children's current behavior was best predicted by parental teaching, however, how children planned to behave when they were adults was best predicted by parents' practices. Children attributed less frequent safety behaviors by their parents than themselves to general attributes of adults and their parent having special skills that made the safety practices less necessary than was true for children. CONCLUSION: These results highlight family influences on children's adoption of safety and risk practices and support the notion of intergenerational transmission of risk behaviors.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".