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Record W1971775619 · doi:10.3138/jvme.33.2.238

An Overview of Veterinary Medical Education in China: Current Status, Deficiencies, and Strategy for Improvement

2006· review· en· W1971775619 on OpenAlexvenueno aff
Jiechao Yin, Guang-Xing Li, Xiaofeng Ren

Bibliographic record

VenueJournal of Veterinary Medical Education · 2006
Typereview
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaAccreditationGovernment (linguistics)Political scienceGlobalizationEconomic growthEuropean unionMedicineVeterinary medicineMedical educationBusinessEconomicsInternational trade

Abstract

fetched live from OpenAlex

Especially in developing countries, the profession of veterinary medicine is closely tied with agriculture and government economic development, the national structure of education, and national public health. Currently, the Chinese veterinary medical educational system and accreditation standards are distinctly different from those of some more developed countries, such as the United States, Japan, or the countries of the European Union. Chinese veterinary education is still closely based on traditional Chinese education approaches and standards, which has led to some deficiencies in the Chinese system. With the development of a stronger economy in China and the growing trend toward globalization, and particularly since China joined the World Trade Organization (WTO), some important questions about China's system of veterinary education are being raised: How can veterinary science develop more rapidly in China? How can it meet the needs of the growing Chinese society? How can China bring its veterinary medical practice more in line with that of other, more advanced countries? This article describes some of the realities of veterinary medical education in China, discusses several existing problems, and puts forward some ideas for possible reforms. It is hoped that by this means those outside China may gain insight into our veterinary education program and that this, in turn, will lead to helpful input from international educators and other professionals to help improve our programs.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.565
GPT teacher head0.632
Teacher spread0.067 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2006
Admission routes1
Has abstractyes

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