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Record W2151685704 · doi:10.5430/ijhe.v2n2p122

The Enlightenments of Educational Ideas of Ancient Academy on Modern Higher Education

2013· article· en· W2151685704 on OpenAlexvenueno aff
Xia Huang, Xi Shen

Bibliographic record

VenueInternational Journal of Higher Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
Fundersnot available
KeywordsMoralityAutonomyIndependence (probability theory)Construct (python library)ChinaSociologyValue (mathematics)PedagogyAdministration (probate law)Higher educationPhilosophy of educationCorporate governanceQuality (philosophy)Political scienceEngineering ethicsLawManagementEpistemologyEngineeringPhilosophyComputer science

Abstract

fetched live from OpenAlex

The ancient academy in China demonstrated some unique educational values, such as the school-running idea of independence and autonomy and the governance by famous experts, the instruction idea of being free and open and focusing on academy and morality cultivation, and the management concept of mind-oriented administration and student autonomy. At present time, Chinese universities have encounterred some difficulties in the process of talents cultivation, such as the administrativization, the incomplete implement of people-oriented concept and the inadequate attention on morality education. As a result, the educational ideas of ancient academy enlighten modern higher education mainly in the following aspects: the university should keep its relative independence, put the student-centered administration into practice, construct academic research atmosphere and promote academic communication, value morality cultivation and foster human spirit, and then the essence of these educational ideas will promote the reform and the development of higher education and improve the quality of talents cultivation in China.

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)0.004
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.390
Teacher spread0.364 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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