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Record W72475251

Транспарентность управления природопользованием как фактор развития территории

2013· article· ru· W72475251 on OpenAlexaboutno aff
Присяжный Михаил Юрьевич, Алексеев Виталий Владиславович

Bibliographic record

VenueТеория и практика общественного развития · 2013
Typearticle
Languageru
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusSocioeconomic developmentTransparency (behavior)State (computer science)Russian federationPolitical scienceGovernment (linguistics)Scale (ratio)Regional scienceEconomic growthEconomyGeographyEconomicsSociologyPopulationLaw
DOInot available

Abstract

fetched live from OpenAlex

The Russian Federation’s focus on the market mechanism of economy functioning should be supported and/or corrected by the reasonable state policy of the socioeconomic development. Taking into account environmental and socioeconomic features of the territories the proper nature management system is being built. The article deals with experience of Canada on formation of the transparency of the state authorities for providing society’s participation in the socioeconomic development of the Northern territories. Development scenarios based upon the cooperation of the government and economic entities with officials of various levels and territorial communities is reasonable to correlate with successfully implemented projects of the global (international), Russian (interregional), republican (regional) and municipal (local) scale or character.

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)0.002
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.028
GPT teacher head0.314
Teacher spread0.286 · 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
Published2013
Admission routes1
Has abstractyes

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