Parental Knowledge of Child Development and the Assignment of Tractor Work to Children
Bibliographic record
Abstract
OBJECTIVES: Many childhood farm tractor injuries occur during the performance of work that was assigned by parents, and some tractor work is beyond the developmental capabilities of children. This has been highlighted recently by a policy statement authored by the American Academy of Pediatrics. The objective of this study was 1) to assess child development knowledge of farm parents who received a new resource, the North American Guidelines for Children's Agricultural Tasks (NAGCAT), and 2) to determine whether this knowledge was associated with use of NAGCAT in the assignment of tractor jobs and with compliance with 2 aspects of the NAGCAT tractor guideline. METHODS: Secondary analysis of data collected during a randomized controlled trial that involved 450 farms in the United States and Canada was conducted. Variables assessed included 1) parental knowledge of child development across several age groups and 3 domains of child development (physical, cognitive, and psychosocial), 2) documentation of the most common tractor jobs assigned to each child, and 3) a report of whether NAGCAT was used in assigning these tractor jobs. RESULTS: High parental knowledge of child development was associated with enhanced use of NAGCAT and fewer violations when assigning tractor work to children. However, even in the presence of high knowledge, some farm parents still assigned to their children work that was in violation of NAGCAT. CONCLUSIONS: Educational interventions by themselves are not sufficient to remove many farm children from known occupational hazards. These findings are discussed in light of the recent policy statement on agricultural injuries from the American Academy of Pediatrics.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".