MétaCan
Menu
Back to cohort
Record W1866530474 · doi:10.19173/irrodl.v10i1.590

Making Education Equitable in Rural China through Distance Learning

2009· article· en· W1866530474 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsAthabasca University
Fundersnot available
KeywordsChinaDistance educationEconomic growthGovernment (linguistics)Basic educationRural areaQuality (philosophy)Information and Communications TechnologyPolitical sciencePopulationGeographyPublic relationsSociologyEconomics

Abstract

fetched live from OpenAlex

The Distance Education Project for Rural Schools (DEPRS) was implemented by the Chinese government between 2003 and 2007 to improve the quality of basic education in rural areas of China, especially in the poorer western provinces. It has been referred to as “the largest ICT project in the world up to now” because “it serves a larger population than any other similar projects and therefore will likely start a far-reaching information revolution in China.” This paper offers a descriptive analysis of the effectiveness and impact of DEPRS, explaining how and why it was implemented as a solution to close the wide gaps in access to high quality basic education. Focusing on the initial achievements of DEPRS, this paper explores if, how, and to what extent the three learning tools employed in DEPRS have improved basic education in remote rural areas.

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.

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)0.007
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.675
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.118
GPT teacher head0.518
Teacher spread0.399 · 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