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Record W4324381046 · doi:10.5539/ass.v19n2p66

Prospects for the Resumption of the Peace Process in Syria

2023· article· en· W4324381046 on OpenAlexvenueno aff
Vassil Stankov

Bibliographic record

VenueAsian Social Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)ConstitutionCorporate governancePolitical scienceOrder (exchange)Political economyLaw and economicsSociologyLawBusinessEconomicsComputer scienceManagement

Abstract

fetched live from OpenAlex

The paper highlights the key features of the conflict in Syria and the reasons for the involvement of a number of regional and global players, whose behavior is driven by strife to protect their interests the best way possible, thus making it indicative of the prospects for resuming the peace process. The paper explores the current attitudes and approaches of the major stakeholders and ventures to analyze the rationale behind their actions in the event of an unfolding comprehensive peace process. Furthermore, the paper makes an assessment of the trends and prospects for a general reduction of hostilities and reopening the peace process vis-à-vis the attempts by Turkey and other important players to restore ties, improve relations and establish a dialogue with the Syrian regime. The paper goes on to reveal the nation-wide and local obstacles that need to be overcome should a genuine attempt be made towards rapprochement, ceasefire and reconciliation as a prelude to pacification and comprehensive discussions about future governance and a new Constitution. Finally, the paper concludes by suggesting a number of indicators worth following in order to anticipate a growing likelihood for reopening the peace process.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

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 studies0.0030.002
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.356
Teacher spread0.333 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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