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Record W4360986287 · doi:10.6575/jila.201812_(93).0001

The Choice at the Crossroads of History: Research on Development Path of Archival Education in Mainland China from 1949 to 1966

2018· article· en· W4360986287 on OpenAlexaff
Yan Zhang

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEducational Reforms and Innovations
Canadian institutionsLibrary and Archives Canada
Fundersnot available
KeywordsChinaMainland ChinaPath (computing)Political scienceHistoryGeographyArchaeologyComputer science

Abstract

fetched live from OpenAlex

The mainstream view of archival field in mainland China is, when the archival education was reconstructed in 1952, the Chinese mainland faced the dilemma of "no teacher, no textbook and no experience". In fact, within the 16 years from 1934 to 1949, the archival education of the Republic of China had left quite a scale of archives education resources to the Chinese Mainland in three aspects, namely educational institution, teachers and monographs. However, such resources that deviated from the expected values were not used initially. Chinese mainland turned to the Soviet Union for help, and completely copied the Soviet archive education model with the help of the Soviet Union. After then, it began to selectively use some of the archive education resources of the Republic of China and began to localize the Soviet archival education model, creating an education system for archives in mainland China which is in line with China's national conditions.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.249
GPT teacher head0.556
Teacher spread0.307 · 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 designQualitative
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
Published2018
Admission routes1
Has abstractyes

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