MétaCan
Menu
Back to cohort
Record W2190926796 · doi:10.33710/sduijes.223871

Sustaining small rural schools via e-learning

2015· article· en· W2190926796 on OpenAlexaffabout
Nadeem Saqlain

Bibliographic record

VenueDergiPark (Istanbul University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDistance educationGlobeThe InternetRural areaConsolidation (business)Rural managementPolitical scienceEconomic growthGeographyMathematics educationPedagogyPublic relationsSociologyBusinessRural developmentPsychologyComputer scienceWorld Wide WebEconomics

Abstract

fetched live from OpenAlex

Many small rural schools have been closed during the reform movement. A mountain of studies suggest that small school have various advantages. Despite these advantages, small schools are still in danger of closure and consolidation. However, the advent of internet is a ray of hope to sustain small schools in rural areas. Many K-12 online programs across the world are providing educational opportunities to students. Most of those virtual schools have focus on urban and suburban students. However, the Centre for Distance Learning and Innovation (CDLI) has been established to provide equitable access to educational opportunities to rural students. The author has outlined a short history of distance education in the province of Newfoundland and Labrador. Various issues of e-learning at the K-12 have been identified. It is also intended that the e-learning model which is being used in the province can provide a model to sustain small schools across the globe.Key words: Virtual schooling, Rural education, Small schools, Distance 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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.041
GPT teacher head0.285
Teacher spread0.244 · 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 designObservational
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
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueDergiPark (Istanbul University)Same topicEducation Systems and PolicyFrench-language works237,207