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Record W3024079910 · doi:10.5430/ijhe.v9n4p13

Comparison of the Graduate Education between Canada and China

2020· article· en· W3024079910 on OpenAlexaffvenueabout
Tao Tang, Maged A. Aldhaeebi, Ebrahim Bamanger

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversity of Waterloo
FundersMinistry of Education of the People's Republic of China
KeywordsGraduate educationChinaGovernment (linguistics)Political scienceGraduate studentsHigher educationEconomic growthScale (ratio)SociologyPedagogyGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

In this study, a comparison of the graduate education program between Canada and China is presented. Compared with some developed countries in Europe and America, Canada's graduate education does not start too early. After World War II, especially in recent decades, its graduate education has developed rapidly. The reason is that under the situation of the rapid development of science, technology, and economy in domestic and foreign scale, the Canadian federal government and provincial government gradually realize the importance of graduate education; therefore, they vigorously support and fund graduate education. China's graduate education has started later than Canada's. However, it has developed rapidly in recent years. Canadian and Chinese graduate education have their distinct characteristics with some similarities and some differences. The development history, present situation and problems, training mode and future development of graduate education in Canada and China are compared, and then some suggestions for the development of graduate education in China are presented accordingly.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.383
Teacher spread0.343 · 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.

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

Citations10
Published2020
Admission routes3
Has abstractyes

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