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Record W1973516506 · doi:10.2527/jas.2007-85-11-2787

The role of livestock in developing countries

2007· article· en· W1973516506 on OpenAlexaboutno aff
Mark A. Mirando, Lawrence P. Reynolds

Bibliographic record

VenueJournal of Animal Science · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsLivestockDeveloping countryBusinessBiologyEcology

Abstract

fetched live from OpenAlex

In this issue of the Journal of Animal Science, you will find an invited review by T. F. Randolph and colleagues of the International Livestock Research Institute, Nairobi, Kenya; the Swiss Tropical Institute, Basel; Cornell University, Ithaca, NY; the National Institute of Public Health, Cuernavaca, Mexico; the University of Toronto, Canada; the International Potato Centre, Lima, Peru; the University of California, Davis; and the International Food Policy Research Institute in Washington, DC. This article is based on a presentation made at the symposium entitled, “International Animal Agriculture: Global Livestock and Poultry Issues” at the Joint Annual Meeting of the American Dairy Science Association, the Poultry Science Association, the Asociación Mexicana de Producción Animal, and the American Society of Animal Science (publisher of the Journal of Animal Science), held July 8–12, 2007, in San Antonio, Texas. We invited Dr. Randolph and colleagues to write this review as part of our response to a request from the Council of Science Editors (CSE) to participate in their Global Theme Issue on Poverty and Human Development (http://www.councilscienceeditors.org/globalthemeissue.cfm). As described by CSE, as part of the Global Theme Issue, “Science journals throughout the world will simultaneously publish papers on this topic of worldwide interest—to raise awareness, stimulate interest, and stimulate research into poverty and human development. This is an international collaboration with journals from developed and developing countries.” However, the purpose of our invitation went beyond responding to the Global Theme Issue of CSE. Our purpose was to highlight the importance of livestock in the global effort to alleviate poverty and promote human health, for those involved in livestock research, for policymakers, and those who are the beneficiaries of these efforts. We also wanted to provide a scholarly analysis of the facts as well as some of the misconceptions concerning the contribution of livestock to the health and economic progress of developing countries. In fact, as Dr. Randolph and colleagues observe in their review, “Animal-source foods are particularly appropriate for combating malnutrition and a range of nutritional deficiencies,” and, “livestock clearly offer the most efficient utilization of resources that would otherwise go unexploited…,” and thereby contribute to economic development as well. Thus, “livestock keeping” has been, and will continue to be, integral to improving the well-being of people in developing countries, both from a health and nutrition perspective and from a socioeconomic one. However, as pointed out by Randolph and co-authors, there is a critical need for objective, scientifically sound studies on the role of and methods to promote improved livestock production in developing countries. We could think of nothing more appropriate than a review on this topic for the Journal of Animal Science as part of this global effort to alleviate the suffering of millions of people. To help ensure that they have the intended impact, this editorial and the review article by Randolph and colleagues are being released as open access publications. We offer our sincere thanks to Dr. Randolph and colleagues for their thorough and balanced review of this important topic and to the reviewers and editors involved in bringing this paper to publication.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.007
GPT teacher head0.239
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2007
Admission routes1
Has abstractyes

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