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Record W2970947061 · doi:10.3968/11218

30 Years on, Has the IMF Helped or Hindered the Jordanian Economy?

2019· article· en· W2970947061 on OpenAlexvenueno aff
Walid Alkhatib, Miss Nafiso Mohamed

Bibliographic record

VenueCanadian social science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityEconomicsBalance of paymentsRemittanceEconomic policyEconomyPolitical scienceDevelopment economicsInternational economicsEconomic growth

Abstract

fetched live from OpenAlex

In spite of the hostile external environment, Jordan has displayed resilience in maintaining internal cohesion in the face of adversity. The combination of the global financial crisis, energy crisis, closure of trade routes resulting to a de facto economic siege, Arab spring regional turmoil, increasing the cost of security, decreases in remittance and the rising oil and food prices have placed substantial pressure on the Jordanian economy and fiscal effort. As a result of the economic crises, Jordan encountered profound macro-economic and structural related issues as well as a severe balance of payments crisis. In the past three decades, Jordan has adopted various reform programs in cooperation with the International Monetary Fund (IMF) in hopes of stabilizing its economy through neo-liberal policies (El-Said, Harrigan, 2009). This paper aims to determine the extent to which IMF programs contributed to Jordan’s economic prosperity in tackling challenges in its macro-economy from 1989 to 2019. The IMF reform programs were supported under several stand-by agreements (SBA’S) and Extended Fund Facility (EFF) arrangements. This paper would discuss what the overall objectives of the reform programs were and whether they were relevant to Jordan’s circumstances. Whether the IMF policies and processes worked in favour of Jordan’s institutional dealings and if Jordan received preference from the IMF concerning their geopolitical considerations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.275
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2019
Admission routes1
Has abstractyes

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