MétaCan
Menu
Back to cohort
Record W4404428551 · doi:10.1080/09644016.2024.2427527

Constructing climate change rentierism in Jordan

2024· article· en· W4404428551 on OpenAlexfundno aff
Marianna Poberezhskaya, Imad El‐Anis

Bibliographic record

VenueEnvironmental Politics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsClimate changeGeographyPolitical scienceClimatologyEnvironmental scienceGeologyOceanography

Abstract

fetched live from OpenAlex

Jordan is exceptionally vulnerable to climate change and has limited adaptive capacities. It is also a non-democratic state with an ubiquitous role for the monarchy that results in narratives that seek to promote the regime’s stability by securing external support in the form of ‘rents’. In this paper we examine how the government ‘rents out’ Jordan’s stability and its engagement with climate change initiatives to the international community through its unintentional use of fearmongering. Jordan’s vulnerability narrative, in particular, highlights its stabilising role in regional affairs (e.g. by hosting refugees from neighbouring countries) and attracts the support of external actors interested in its stability. While rent-seeking behaviour could serve as a short-term solution to the imminent threats imposed by climate change, it can also reinforce authoritarianism and divert attention away from long-term sustainable adaptation and mitigation activities.

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)0.003
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 score0.018
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.014
Scholarly communication0.0070.004
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental PoliticsSame topicTransboundary Water Resource ManagementFrench-language works237,207