Current status, challenges and prospects for dairy goat production in the Americas
Bibliographic record
Abstract
Dairy goat production continues to be a socially, economically and culturally important part of the livestock industry in North, Central and South America and the Caribbean islands. Goat milk, cheese and other dairy products offer consumers food products with nutritional, health and environmental benefits. In North America, Mexico produces the greatest volume of goat milk, but most is for family or local consumption that is typical of a mixed farming system adopted by subsistence farmers in dry areas. The United States is not yet a large global goat milk producer, but the sector has expanded rapidly, with dairy goat numbers doubling between 1997 and 2012. The number of dairy goats has also increased dramatically in Canada. Commercial farms are increasingly important, driven by rising demand for good quality and locally sourced goat cheese. In South America, Brazil has the most developed dairy goat industry that includes government assistance to small-scale producers and low-income households. As of 2017, FAO identified Haiti, Peru, Jamaica, and Bolivia as having important goat milk production in the Western Hemisphere. For subsistence goat producers in the Americas on marginal land without prior history of chemical usage, organic dairy goat production can be a viable alternative for income generation, with sufficient transportation, sanitation and marketing initiatives. Production efficiency, greenhouse gas emission, waste disposal, and animal welfare are important challenges for dairy goat producers in the Americas.
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 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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".