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Record W4213291661 · doi:10.5281/zenodo.5336996

SOCIAL POLICY ON ORGANIZATION OF EMPLOYMENT IN UZBEKISTAN IN PANDEMIC CONDITIONS

2021· article· en· W4213291661 on OpenAlexaff
Akbarova Laylo Upashevna

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsTransport Canada
Fundersnot available
KeywordsPandemicSocial policySocial organizationCoronavirus disease 2019 (COVID-19)Political scienceBusinessEconomic growthDevelopment economicsSociologyEconomicsSocial scienceMedicine

Abstract

fetched live from OpenAlex

Annotation. The article outlines the priorities for employment through regulation of the labor market and examines the results of reforms implemented in Uzbekistan in recent years. In particular, the impact of quarantine measures imposed in connection with the COVID-19 pandemic on the labor market has been theoretically studied, including the suspicion of unemployment among the population, especially voluntary redundancies, staff reductions or bankruptcy of enterprises and organizations. The structural and functional advantages of the institutional framework for the prevention of exclusion due to the presence of (breakage) and their implementation in practice were highlighted.

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: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

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 studies0.0130.007
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.069
GPT teacher head0.299
Teacher spread0.229 · 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
Published2021
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicHermeneutics and Narrative Identity→French-language works237,207→