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Record W3160126495 · doi:10.3968/12141

An Exploration of the Essence of Open Education

2021· article· en· W3160126495 on OpenAlexvenueno aff
Jinying Chen

Bibliographic record

VenueCross-cultural communication · 2021
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsOpen educationLifelong learningLearning societyOpen societyCore (optical fiber)ChinaOpen learningSociologyPolitical sciencePedagogyPublic relationsEngineeringTeaching methodLawCooperative learning

Abstract

fetched live from OpenAlex

A platform to help the public climb up the social ladder, open education promotes education equality, providing every member of society with the opportunity to receive higher education and serving for people’s lifelong learning and development. In practice, people with different educational backgrounds are admitted to this education system, which appears to be seemingly unpersuasive. Despite a history of 40 years, the Open University of China does not seem to be widely recognized by the society. Therefore, it is necessary explore the essence of open education from its very beginning. This paper reviews the evolution of open education and explores its essence, definition and academic debates with the aim to reach the core of open education.

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)0.006
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.044
Scholarly communication0.0100.016
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.112
GPT teacher head0.473
Teacher spread0.361 · 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
Published2021
Admission routes1
Has abstractyes

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