MétaCan
Menu
Back to cohort
Record W3123623134 · doi:10.1016/j.aos.2012.09.002

The influence of the institutional context on corporate illegality

2017· article· en· W3123623134 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

VenueInstitutional Research Information System (University of Udine) · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHerdingCompromiseScrutinyHumiliationJudgementBusinessCognitionVigilance (psychology)Independence (probability theory)Context (archaeology)Social psychologyPublic relationsPsychologyLaw and economicsPolitical scienceCognitive psychologyEconomicsLaw

Abstract

fetched live from OpenAlex

This paper examines the relationship between the institutional environment and sustained corporate illegality. We find that cognitive assumptions generate expectations that can, under specific circumstances, induce organizations to amplify illegal actions and that serve to lessen regulatory scrutiny. We also find that, once initiated, illegal actions can become hidden because of institutionalized practices that enable their concealment and that weaken the prospect of detection. These processes and effects are particularly noticeable in networks of professional regulators who become mutually over-confident and over-influenced by each other to the extent that their independent critical assessments and judgements are compromised. Mechanisms of mimetic herding and social humiliation compromise independence of judgement. Networks of interacting professionals are thus vulnerable to a collectively induced lowering of regulatory vigilance.

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)0.010
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.005
Scholarly communication0.0000.003
Open science0.0020.001
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 head0.450
GPT teacher head0.421
Teacher spread0.028 · 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