MétaCan
Menu
Back to cohort
Record W4401421978 · doi:10.31578/jebs.v9i2.314

A Competitive Analysis of International Students Attraction Practices in Georgia and World Leading Students’ Destination Countries (Benchmark of the Best Cases)

2024· article· en· W4401421978 on OpenAlexaboutno aff
Goderdzi Buchashvili, Ekaterine Kvantaliani

Bibliographic record

VenueJournal of Education in Black Sea Region · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCentral Asia Education and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsAttractionBenchmark (surveying)MarketingMathematics educationRegional scienceAdvertisingBusinessPolitical scienceGeographyPsychologyCartography

Abstract

fetched live from OpenAlex

Student worldwide mobility has increasingly become an important indicator for the degree of internationalization and reputation of higher education institutions. The universities focus on the attraction of international students as a potential source of financial income and prestige of their educational provisions. Massive global competition between countries regarding attraction of oversea students have been fluctuating during decades. Nowadays the US, UK, Canada, Germany (the top recruiter countries) have been caught up and even overtaken by China, India, Malaysia. The central question of discussion is how the sender countries (China, Turkey) managed to become receivers of international students and what are the main issues small countries, like Georgia, can benchmark from them. Moreover, the US and UK have accumulated the best experiences that might be shared with the rest of the world. As international student mobility has become intensive and economically beneficial for the Georgian higher education institutions the main goal of the study is to examine all those trends and marketing strategies that are popular and rational for the Georgian context. The core aim of the research is to identify gaps in local context and offer further development opportunities for the Georgian universities in terms of increasing international students’ recruitment in Georgia and transforming the small country into the ‘regional educational hub’.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.421
Teacher spread0.383 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Education in Black Sea RegionSame topicCentral Asia Education and CultureFrench-language works237,207