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Record W3154911345 · doi:10.5539/ibr.v14n5p49

Study on the Strategy of Constructing Compliance Management System in Large State-owned Logistics Enterprises

2021· article· en· W3154911345 on OpenAlexvenueno aff
Liu Zhongmin

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCompliance (psychology)Process (computing)Control (management)Process managementOrder (exchange)Risk analysis (engineering)Risk managementOperations managementIdentification (biology)Computer scienceFinanceManagementEngineeringEconomics

Abstract

fetched live from OpenAlex

In order to promote the all-round compliance management in central enterprises, accelerate the management improvement in accordance with law, and strive to construct the central enterprises under the rule of law to ensure the sustainable and sound development, on November 2,2018, the SASAC issued the “Central Enterprise Compliance Management Guidelines((Trial), Subsequently, the local SASAC also issued relevant guidance documents, such as on December 28,2018, the Shanghai SASAC issued the “Shanghai SASAC Supervision Enterprise Compliance Management Guidelines (trial)”. As for a large state-owned logistics enterprise, the daily operation and management involves various links and wide range, the establishment of compliance management system is particularly significant. This paper takes SASAC's guidelines as the criterion, carries out analysis on the previous management compliance and process control, the post-management risk identification and risk control, prevention and pre-warning, etc., combing the process and organizational structure of compliance management system construction, so as to build a complete compliance management system framework, and finally put forward effective recommendations and measures for compliance management in large state-owned enterprises.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.394
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.151
GPT teacher head0.374
Teacher spread0.223 · 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.

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
Published2021
Admission routes1
Has abstractyes

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