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Record W2327999994 · doi:10.12737/545

Practice of compensation in the foreign design and survey organizations

2013· article· en· W2327999994 on OpenAlexaboutno aff
Рогожникова, Yuliya Rogozhnikova

Bibliographic record

VenueManagement of the personnel and intellectual resources in Russia · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalaryIncentiveBusinessGermanWork (physics)PaymentCompensation (psychology)Joint ventureRedistribution (election)AccountingMarketingFinanceEconomicsEngineeringCommerceMarket economyPolitical science

Abstract

fetched live from OpenAlex

Article contains the analysis related to applied elements of system of payment and work incentives in the design and survey organizations of France, Germany, Canada, and also in the joint German-Russian venture. The considered foreign organizations take leading positions in branch of transport design in the international market and can compete with Russian companies in the market of design and exploration work and on a labor market of technical specialists (design engineers, architects and others) and managers (CPEs — chief project engineers, CPAs —chief project architects). The analysis of foreign experience in area of compensation and social policy allows to draw conclusions and to develop recommendations for the domestic companies about redistribution of financial means in structure of expenses for the personnel and transfer of organizations’ expenses related to social package to employees’ salary.

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)0.017
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.038
GPT teacher head0.290
Teacher spread0.253 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

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