Estimation of the value of Johne’s disease (paratuberculosis) control to Canadian dairy producers
Bibliographic record
Abstract
Johne's disease (JD), or paratuberculosis, is an infectious disorder primarily associated with cattle and sheep and resulting in significant economic losses for dairy producers. The dairy cattle herd-level prevalence in Canada has recently been estimated to be greater than 40%, but the willingness to pay for JD control practices such as testing-and-culling and vaccination among Canadian dairy producers is unknown. This study used confidential cost-of-production data from the Canadian Dairy Commission to develop a Canadian dairy production model incorporating feed, land, labor, and machinery. A second dataset from a nationally distributed questionnaire (closed in March 2020) was used to estimate individual dairy producer valuations of the reduced per-cow cost of milk production that would result from JD control. This is a novel application of compensating variation and equivalent variation (CV and EV), with dairy producers framed as consumers of production inputs and milk output as a proxy for utility. Assuming a within-herd prevalence of 12.5% and a 50% reduction of that prevalence over 10 years, it was estimated JD control has an annual value of CA$28 per cow for the average Canadian dairy producer. Within-herd prevalence, the effectiveness of control at reducing within-herd prevalence, and the time required to achieve that reduction were identified as important factors. With the same assumption of 12.5% within-herd prevalence but with 100% reductions in that prevalence, estimated values ranged from over CA$55 to over CA$90 per cow per year depending on the timeframe of the control program. When assuming a 10-year period required to achieve control, the estimated values exceeded CA$90 per cow per year in various scenarios for herds with higher within-herd prevalence (greater than 20%).
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".