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Record W3160724299 · doi:10.23977/aetp.2021.52016

Comparative Analysis of Academic Research and Scientific Research Management in Chinese and Australian Universities

2021· article· en· W3160724299 on OpenAlexvenueno aff
Junru Jiang, Ziying Zhao, Yutong Liu, Chunyan Qiu, Yang Liu

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsChinaCurriculumPolitical scienceEngineering ethicsHigher educationClass (philosophy)Public relationsSociologyEngineeringPedagogyComputer science

Abstract

fetched live from OpenAlex

The academic research and scientific research management play a key role in the scientific research direction, project application, transformation of scientific research achievements and academic exchanges of universities. In Australia, which is powerful in education, the industrialization of education with eight Australian schools as the core is becoming more and more complete, and its scientific research and talent cultivation mechanisms are becoming more scientific and efficient. The core of scientific research management in Australian universities is people-oriented, paying more attention to the cultivation of talents, and having a relatively complete scientific research platform management mechanism independent of universities. Concisely, in China, due to its large number of students, the Chinese universities often focus on basic teaching and curriculum settings. The number of scientific researchers in universities is scarce and there is a lack of a favourable scientific research environment. In recent years, with the gradual implementation of the construction of double first-class colleges and universities, the academic research and scientific research management of our country's universities have also been continuously developed. Taking the universities in Jilin Province as an example, this paper compares the academic research and scientific research management of universities in China and Australia, points out their advantages and disadvantages and puts forward some suggestions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.387
GPT teacher head0.689
Teacher spread0.302 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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