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Record W7132548798

性别多样化为什么重要? 中国上市公司中的性别多样性和欺诈行为现状

2019· article· W7132548798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCEIBS Institutional Repository · 2019
Typearticle
Language
FieldSocial Sciences
TopicRegional Development and Environment
Canadian institutionsYork University
Fundersnot available
KeywordsDiversity (politics)Work (physics)Natural (archaeology)Interpretation (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

在上一期专栏文章中,我们从性别与道德、风险厌恶以及性别多样性角度三方面阐释了董事会中的性别多元化对欺诈频率和严重程度有哪些影响,并且我们还区分了这些因素在男性主导产业与女性主导产业中的不同表现。我们得出了三个假设:公司董事会中的女性成员减少了欺诈的频率,而在董事会中女性比例最高为50%的公司中,这种影响正在减弱;董事会的性别多样性减少了投资者对欺诈声明的负面反应;女性董事在男性主导行业的影响将强于女性主导的行业。 本文根据 Douglas Cumming,T.Y. Leung,Oliver M. Rui. Gender Diversity and Securities Fraud. Academy of Management Journal, 2015, 1572-1593. 论文翻译而成。刘心洁编译,论文原作者之一芮萌教授对原文进行了适当改写。

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.008

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 head0.011
GPT teacher head0.224
Teacher spread0.214 · 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