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Corporate Wrongdoing and Board Leadership Structure: The Stories of WestJet and Hewlett-Packard

2017· article· en· W2766847477 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAcademy of Management Proceedings · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSecurities Regulation and Market Practices
Canadian institutionsSimon Fraser UniversityDalhousie University
Fundersnot available
KeywordsWrongdoingProfitability indexExtant taxonOrder (exchange)ManagementCorporate governanceAccountingBusinessPolitical scienceEconomicsLawFinance

Abstract

fetched live from OpenAlex

Based on underpinnings from the extant literature on negotiated order theory and board leadership structure, we propose a model to explain the relationship between board leadership structure, corporate wrongdoing (Internet snooping and pretesting/social engineering), and company performance. In order to illustrate our proposed model, we develop two mini cases on WestJet in Canada and Hewlett Packard in the United States, where serious corporate wrongdoings had taken place at the behest of the board leaders. The comparison of the cases suggests that both CEO duality and CEO/Chair split can contribute equally to corporate wrongdoing. Consistent with the theoretical model, the comparison also illustrates that corporations are able to withstand the adverse effects of wrongdoings and regain investor confidence and profitability through the symbolic and substantive reversal of their leadership structures following a scandal. The study’s implications are given.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.546

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 studies0.0000.001
Scholarly communication0.0010.003
Open science0.0000.001
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 head0.085
GPT teacher head0.269
Teacher spread0.184 · 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