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Record W4402477954 · doi:10.33920/pol-01-2408-05

Analysis of causes and sources of growing tension in labor relations and increasing labor conflicts in medical institutions in the healthcare sector

2024· article· en· W4402477954 on OpenAlexaboutno aff
Aleksandr Anatolievich Dovganenko

Bibliographic record

VenueSocial naja politika i social noe partnerstvo (Social Policy and Social Partnership) · 2024
Typearticle
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsAllowance (engineering)Quarter (Canadian coin)Russian federationLabor relationsPaymentHealth carePolitical scienceTrade unionBusinessIndustrial relationsLabour economicsPublic relationsEconomic policyEconomicsLawOperations managementFinance

Abstract

fetched live from OpenAlex

The article is based on research by the Labor Conflicts Center (St. Petersburg). In the second quarter of this year, a new increase in tension in social and labor relations was noted, and numerous protests by physician assistants and drivers, demanding the payment of a new special social allowance, were registered. The industry trade union of the Federation of Independent Trade Unions of Russia believes that the measures to support those employed in the industry announced by the President of the Russian Federation have not been fully implemented, which contributes to discontent among employees of medical institutions.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.105
GPT teacher head0.430
Teacher spread0.325 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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