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Record W4312101000

FOREIGN UNIVERSITIES IN QATAR: A CRITICAL REVIEW OF POLICY AND SUSTAINABILITY ISSUES

2019· review· en· W4312101000 on OpenAlexaboutno aff
Fethi B. Jomaa Ahmed

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typereview
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityForeign policyPolitical scienceBusinessLaw
DOInot available

Abstract

fetched live from OpenAlex

Qatar is transitioning toward knowledge society and aims at becoming a hub for international education. The Permanent Constitution and the Nation Vision 2030 of Qatar explicitly refer to the role of government in promoting sound education as making it the prime driver of human, social and economic development. The government has invested 3.5% of its GDP in education. Since 1998, Qatar has succeeded in contracting 11 International foreign universities to open branches in Qatar. These International Branch Campuses (IBCs) include Texas A&M University, Weill Cornell Medical College, Georgetown University, University College London and University of Calgary. The IBCs offer a range of specializations and degree programs such as medicine, engineering, foreign affairs, journalism, and tourism. Qatar spends more than US$400 million annually on the six US branch campuses only excluding construction expenses. Hence, this study attempts to examine Qatar’s policy on the IBCs and investigate its sustainability. The author focuses on discussing critical policy issues including English as language of instruction, mixed-gender education, and the ‘glocalization’ of the IBCs. Moreover, he addresses sustainability issues related to the IBCs such as the political will, diversification of the economy, and the contribution of the IBCs to Qatar’s society. Ultimately, the author is enthusiastic that this library-based, theoretical and critical study would provoke more scholarly debates on Qatar’s unique model of hosting foreign universities campuses.

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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0030.001
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 head0.368
GPT teacher head0.647
Teacher spread0.279 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2019
Admission routes1
Has abstractyes

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