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Record W2001251689 · doi:10.5539/ibr.v1n3p32

The Cultivation of Enterprise Accountants in the Era of Knowledge Economy

2009· article· en· W2001251689 on OpenAlexvenueno aff
Wenjun Chen, Yehua Yue

Bibliographic record

VenueInternational Business Research · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge economyMoralityWonderScholarshipConsciousnessBusinessQuality (philosophy)Information economyNetwork economyAccountingEconomicsEconomyPolitical scienceEconomic growthLaw

Abstract

fetched live from OpenAlex

Knowledge economy, as well as circular economy, has been the trend of the economic development of the world since the 21st century. The development of knowledge economy requires people to strengthen their ability of replacing material resources with intellectual resources, realizing that participants in the economic activities are better educated. With knowledge economy coming, the society is eager for the high-quality people. No doubt, enterprise accountants are one of the different kinds of talents. But we may wonder what an accountant should have to meet the high requirements of knowledge economy. Consequently, this paper which combines the theory with the practice of enterprise accountants, deeply analyzes the problem of accountants’ cultivation by an all-round and developing viewpoint from four aspects that is morality, consciousness, talent, and scholarship. It aims at making it possible for accountants to promote their cultivation to proper the accounting cause in the era of knowledge economy.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.022
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.358
Teacher spread0.312 · 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 designQualitative
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
Published2009
Admission routes1
Has abstractyes

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