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Record W4388495752 · doi:10.1080/13530194.2023.2279332

Responding to Climate Change in Jordan: understanding institutional developments, political restrictions and economic opportunities

2023· article· en· W4388495752 on OpenAlexfundno aff
Imad El‐Anis, Marianna Poberezhskaya

Bibliographic record

VenueBritish Journal of Middle Eastern Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
FundersKementerian Energi Dan Sumber Daya MineralMinistry of Earth SciencesMinistry of Education, IndiaTrent UniversityMinisterstvo Průmyslu a ObchoduNottingham Trent University
KeywordsClimate changePoliticsVulnerability (computing)Political scienceAuthoritarianismElitePsychological resiliencePolitical economy of climate changeDevelopment economicsPolitical economyEconomic growthDemocracyEconomics

Abstract

fetched live from OpenAlex

Jordan is one of the world's most resource-poor, arid and freshwater-stressed countries with climate change aggravating these challenges further.We argue that due to Jordan's climate change vulnerability and low levels of resilience, as well as its vital role in Middle Eastern politics, it is necessary to examine how climate change policies are approached in the kingdom.Based on a thematic analysis of official climate change policy documentation and elite interviews, we find that climate change problems are portrayed as important in Jordan, but the policymaking and implementation processes face significant challenges.The main predicaments are: the prioritization of short-term political and economic interests, over-reliance on external actors, limited financial, technical and knowledge capacities, and a lack of coordination between the key public sector stakeholders.Furthermore, as with other authoritarian states, Jordan's ability to respond to climate change is influenced by restrictions stemming from the governing regime's prioritization of its own survival.

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)0.005
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.305
GPT teacher head0.357
Teacher spread0.052 · 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 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

Citations14
Published2023
Admission routes1
Has abstractyes

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Same venueBritish Journal of Middle Eastern StudiesSame topicTransboundary Water Resource ManagementFrench-language works237,207