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Record W2767479252 · doi:10.1017/s1537781417000299

100 YEARS OF JOHN DEWEY AND EDUCATION IN CHINA

2017· article· en· W2767479252 on OpenAlexaff
Grace Xinfu Zhang, Ron Sheese

Bibliographic record

VenueThe Journal of the Gilded Age and Progressive Era · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicPragmatism in Philosophy and Education
Canadian institutionsYork University
Fundersnot available
KeywordsChinaContext (archaeology)DemocracyPoliticsMemorizationSociologyPolitical scienceSocial scienceHistoryLawPsychologyMathematics education

Abstract

fetched live from OpenAlex

Only a few years following the publication ofDemocracy and Education, from May 1919 to July 1921, John Dewey traveled and lectured in China. He arrived an already famous American psychologist, philosopher, and educator; but over the course of the years after his departure, that fame diminished, turning to infamy in the 1950s and 1960s, only to be somewhat restored in recent decades. The changing attitudes of the Chinese to Dewey and his ideas are associated with the changing, and often tumultuous, cultural and political context for education in China from the time of his visit through the following century. Hu Shi and Tao Xingzhi, PhD students of Dewey at Columbia University, were prominent Chinese educators who adapted Dewey's educational concepts to the Chinese environment, and their work continues to influence educational debate in China today. While there is desire among many contemporary educators for educational reforms that would be in line with Dewey's principles, there are equal or greater pressures for maintaining systems focused on examinations and memorization.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.010
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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 designNot applicable
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

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

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