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Corporate governance and business ethics

2015· article· en· W2284251940 on OpenAlexaff
Douglas R. McKay, Romy Nitsch, Daniel A Peters

Bibliographic record

VenuePlastic Surgery · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of OttawaQueen's University
Fundersnot available
KeywordsBusiness ethicsCorporate governanceBusinessAccountingEngineering ethicsPolitical sciencePublic relationsEngineeringFinance

Abstract

fetched live from OpenAlex

T he primary objective of a corporation is to increase shareholder value. Successful corporations must operate within society; to that end, they must maintain the values and norms of the society in which they operate. Volkswagen has been the unfortunate recipient of a great deal of press time lately. In case you missed the details, it recently came to light that Volkswagen knowingly deceived the United States Environmental Protection Agency (EPA) with respect to nitrous oxide (NOx) engine emission for their TDI engines. The company programmed the vehicles to favourably behave differently during EPA testing. The engines actually exceeded emission test levels during every day use by roughly 40 fold. The number of affected vehicles is not small -approximately 11 million cars worldwide. While the old adage goes that there is no such thing as bad publicity, the company's publically traded market share losses topped 14 billion during the fallout, suggesting otherwise.

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)0.007
metaresearch head score (Gemma)0.336
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.336
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.545
GPT teacher head0.403
Teacher spread0.142 · 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 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
Published2015
Admission routes1
Has abstractyes

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