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新三板扩容对挂牌企业盈余管理行为影响研究

2016· article· W7131840588 on OpenAlexaff
夏子航, Dengbiao Chen, 陈海涛

Bibliographic record

VenueCEIBS Institutional Repository · 2016
Typearticle
Language
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsCentre Casa
Fundersnot available
KeywordsProcess (computing)Identification (biology)Product (mathematics)

Abstract

fetched live from OpenAlex

本文以2012-2014年全国中小企业股份转让系统挂牌企业为研究样本,基于自然事件研究的思路,考察新三板扩容及该背景下做市商制度对公司应计盈余管理与真实盈余管理行为的影响,以此揭示新三板制度发展对挂牌公司盈余质量的作用效果。研究发现:新三板扩容显著降低了挂牌企业的应计盈余管理及真实盈余管理程度;但是在高速扩容之下,做市商制度引入在一定程度上反而加剧了企业进行应计盈余管理与真实盈余管理,股票流动性提升后,企业实施费用操控的真实盈余管理水平也明显提升。

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.197
Teacher spread0.188 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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