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Foreign experience of social protection of combatants

2025· article· en· W4410463040 on OpenAlexaboutno aff
Володимир САВКА

Bibliographic record

VenueSocial pedagogy theory and practice · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Biological Research in Conflict Zones
Canadian institutionsnot available
Fundersnot available
KeywordsComputer securityComputer science

Abstract

fetched live from OpenAlex

The article analyses the experience of Poland, Spain, Austria, France, Italy, Germany, USA, Denmark, Israel, Croatia, Australia, Canada, and South Korea in the social protection of combatants and identifies the specifics and common features of this system. It is emphasized that the social protection of combatants in foreign countries combines the system of state social protection of the population and civil society institutions. Its characteristic feature is the involvement of local authorities in the implementation of ensuring the social needs of combatants on the ground, the use of the possibilities of public-private partnership mechanisms. It is noted that the direct beneficiaries of social protection of combatants are territorial communities. It is noted that in the conditions of the Russian-Ukrainian war, a social caste of military personnel has formed who need the provision of social services, provision of various social benefits, compensations, and guarantees. It is emphasized that the system of social protection of combatants in Ukraine requires: mobilization of resources; combining the efforts of all stakeholders, including government, business, and the public; creating favourable conditions for the successful return of veterans to civilian life and restoring their active participation in community life. It is noted that the identified common features of social protection of combatants in foreign countries provide an opportunity to accumulate knowledge, practice, methods, technologies, and innovations that can help solve certain problems and tasks related to social protection of combatants in our country.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.398
Teacher spread0.347 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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