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Record W2991080003 · doi:10.5539/jpl.v12n4p70

Traditional State Functions, Their Specificity and Types: Historical Review and Socio-Cultural Characteristics

2019· article· en· W2991080003 on OpenAlexvenueno aff
Valentin Ya. Lyubashits, Alexey Yu. Mamychev, Nikolai V. Razuvaev, Alexander V. Osipov, Natalya Fedorova

Bibliographic record

VenueJournal of Politics and Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSecurity, Politics, and Digital Transformation
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsArgumentation theoryState (computer science)NormativeContext (archaeology)EpistemologyState functionValue (mathematics)Function (biology)PoliticsSociologyPolitical scienceLawMathematicsHistoryPhilosophy

Abstract

fetched live from OpenAlex

The article analyzes the essence of the traditional state functions, their specificity and key differences in comparison with the activities and tasks of the modern state. Discussion of the differences and the argumentation of the types and specificity of the traditional state functions is carried out by the authors on the basis of systematization of various historical and legal studies, political and legal monuments. The article explains that it is possible for each traditional state to identify a number of special functions having historical and typological specificity and a specific historical characteristic. These special functions deepen and concretize the universal (general) function of the state, based on its purpose and thus embodying the essence of the state as a social institution. The authors demonstrate, in a specific context, that the functions of the traditional state as a “base core” form an affective and traditionalist orientation in public power; in contrast to the modern functions of the state, having a value-normative orientation and a goal-rational activity component.

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)0.003
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.015
Science and technology studies0.0010.005
Scholarly communication0.0050.006
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.280
Teacher spread0.231 · 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
GenreReview

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

Citations2
Published2019
Admission routes1
Has abstractyes

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