MétaCan
Menu
Back to cohort

Defensive Practice Adoption in the Face of Organizational Stigma: Impression Management and the Diffusion of Stock Option Expensing

2012· article· en· W1514546248 on OpenAlex
Edward J. Carberry, Brayden G King

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

VenueJournal of Management Studies · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsDeviance (statistics)AccountingCorporate governanceImpression managementLegitimacyBusinessPublic relationsShareholderDismissalStock (firearms)Face (sociological concept)SociologyPsychologySocial psychologyPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

Abstract Although most diffusion research focuses on firms adopting new practices to maintain their legitimacy, this paper examines a setting in which firms adopted a controversial practice to defend themselves against challenges relating to corporate deviance. We argue that understanding defensive adoption requires attending to both the dynamics of organizational stigma and impression management, and test our theoretical claims by analysing the diffusion of an accounting practice, stock option expensing ( SOPEX ), following the E nron scandal. We first provide evidence that the media and shareholder activists transformed the practice into a defensive device by theorizing it as a solution to problems relating to corporate fraud and corporate governance. Using event history analysis, we then show that corporations that became targets of stigma‐inducing threats were more likely to adopt SOPEX and that the media were a key force channelling these threats.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.269

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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