MétaCan
Menu
Back to cohort
Record W7128476051 · doi:10.64903/1480-6800-21.4.299

Can Water Mitigate the Palestinian-Israeli Conflict? – the Case for Environmental Peacemaking

2018· article· W7128476051 on OpenAlexvenueno aff
Mona Farag

Bibliographic record

VenueArab world geographer · 2018
Typearticle
Language
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationPeacemakingEnvironmental securityOrder (exchange)Argument (complex analysis)ScarcityConflict resolutionWater resources

Abstract

fetched live from OpenAlex

Water resources have always occupied an important role in the bilateral negotiations of the Middle East peace process, as it defined the water issues between Israel and the Palestinian territories. This paper aims to shed light on the possibility of whether environmental concerns are an efficient mechanism in bringing conflicting countries to the bargaining table. This paper will argue that issues over water scarcity can be resolved peacefully through international cooperation and negotiation, rather than through military force. The paper will provide an assessment of geographical case studies related to the water issue (which serves as the empirical background of this paper), and will support the argument that environmental cooperation can be used to promote peace as opposed to peace being a prerequisite for environmental cooperation. The anticipated results will consider the current complications of the recent conflict within the region in order to assess the degree of success in including environmental security issues within the conflict resolution negotiations.

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)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0080.010
Open science0.0010.006
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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 designTheoretical or conceptual
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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueArab world geographerSame topicTransboundary Water Resource ManagementFrench-language works237,207