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Record W4413335039 · doi:10.1080/17419166.2025.2544264

Threats to Social Cohesion in Times of New Wars

2025· article· en· W4413335039 on OpenAlexaff
Stanisław Kowalkowski, Danuta Kaźmierczak, Mirosław Laskowski

Bibliographic record

VenueDemocracy and Security · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsNational Capital Commission
Fundersnot available
KeywordsCohesion (chemistry)Political sciencePolitical economyComputer securityLaw and economicsSociologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

The process of globalization and polarization of the world contributes to the change of security environment in which a hierarchically structed and territorially based state is weakened and a new social condition is created promoting relentless violence, the chaotic and volatile mixture of identities, ideologies, organized crime, terrorism and other forms of violence – the world of new wars. These threats directly target social cohesion, which can be understood as trust and cooperation of individuals, groups and societies working toward common goals – prosperous and safe state and the world. The authors of that paper make an attempt to analyze how nowadays social cohesion is challenged by the new wars from political, economic, social, technological, legal, and environmental perspectives (PESTLE). The analysis will help to identify the threats to social cohesion in the above-listed areas of human activity.

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)0.002
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.004
Open science0.0000.006
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 head0.024
GPT teacher head0.268
Teacher spread0.244 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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