Evaluating Swine Injection Technologies as a Workplace Musculoskeletal Injury Intervention: A Study Protocol
Bibliographic record
Abstract
Intensification of modern swine production has led to many new technologies, including needleless injectors. Although needleless injectors may increase productivity (by reducing injection time) and reduce needlestick injuries, the effect on risk for musculoskeletal disorders is not clear. This project will compare conventional needles with needleless injectors in terms of cost, productivity, injury rates, biomechanical exposures, and worker preference. Muscle activity (EMG) and hand/wrist posture will be measured on swine workers performing injection tasks with both injection methods. Video recordings during the exposure assessments will compare the duration and productivity for each injection method using time-and-motion methods. Injury claim data from up to 60 pig barns will be analyzed for needlestick and musculoskeletal injuries before/after needleless injector adoption. Workers and managers will be asked about what they like and dislike about each method and what helps and hinders successful implementation. The information above will be input into a cost-benefit model to determine the incremental effects of needleless injectors in terms of occupational health, worker preference, and the financial "bottom line" of the farm. Findings will be relevant to the swine industry and are intended to be transferable to other new technologies in animal production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".