Safety guidelines for youth agricultural work in the United States: A description of the development and updating process
Bibliographic record
Abstract
To reduce the prevalence of youth injuries and fatalities in agricultural settings, safety professionals considered developing a guideline-focused intervention for how and when youth should conduct farm chores. In 1996, the process to create guidelines started, which then expanded to include professionals from the United States, Canada, and Mexico. This team used a consensus driven approach to develop the guidelines and launch the North American Guidelines for Children's Agricultural Tasks. By 2015, research related to the published guidelines indicated a need to incorporate new empirical evidence and develop dissemination plans based on new technologies. The process for updating the guidelines was supported by a 16-person steering committee and used content experts and technical advisors. The process yielded updated and new guidelines, now called Agricultural Youth Work Guidelines. This report responds to request for further details on the development and update of the guidelines and describes the genesis of the guidelines as an intervention, the process for creating guidelines, recognition of the need to update guidelines based on research, and the process for updating guidelines to assist in others engaged in similar types of interventions.
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 | 0.088 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".