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Record W4383652689 · doi:10.5539/jsd.v16n4p92

Saudi Arabia’s “Vision 2030”: Structural Reforms and Their Challenges

2023· article· en· W4383652689 on OpenAlexvenueno aff
Nitish Kumar

Bibliographic record

VenueJournal of Sustainable Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringPoliticsRevenueEconomicsPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

This paper assesses the Saudi crown prince's visionary mega-project, "Vision 2030," superimposed as a new form of a social contract to diversify the country's economy and end dependency on oil revenue. The project sets to revive the long-staggering economy and propel the indicators of all sectors above the international averages. Concomitantly, the vision faces a colossal challenge as the kingdom is wheeled by authoritarian monarchical Islamic values that repudiate the concept of modernity, the final corollary of the prince's vision. This paper primarily assesses the education and healthcare system management based on the old social contract and seeks possible changes or restructuring according to "Vision 2030" objectives. The paper also looks into managing water shortages which are doomed to become more acute with the launch of mega infrastructural development projects. Further, this paper found that "Vision 2030" is steadily pushing boundaries, albeit there are impeding challenges ranging from the availability of skilled professionals to social, cultural and religious intransigence. Nevertheless, it can be convincible to argue that the cultural, social and political reformation is conceivable unless the citizenry has a strong will and vision regardless of how tumultuous the transition is, which would, in turn, help in streamlining the economic growth of the kingdom.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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