MétaCan
Menu
Back to cohort
Record W2621210202 · doi:10.1177/0018726718809400

Inserting professionals and professional organizations in studies of wrongdoing: The nature, antecedents and consequences of professional misconduct

2018· article· en· W2621210202 on OpenAlex
Claudia Gabbioneta, James Faulconbridge, Graeme Currie, Ronit Dinovitzer, Daniel Muzio

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

VenueHuman Relations · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMisconductWrongdoingProfessional conductPublic relationsLanguage changePhenomenonProfessional associationPsychologyCriminologyPolitical scienceSocial psychologyLawEpistemology

Abstract

fetched live from OpenAlex

Professional misconduct has become seemingly ubiquitous in recent decades. However, to date there has been little sustained effort to theorize the phenomenon of professional misconduct, how this relates to professional organizations, and how this may contribute to broader patterns of corruption and wrongdoing. In response to this gap, in this contribution we discuss the theoretical and empirical implications of analyses that focus on the nature, antecedents and consequences of professional misconduct. In particular, we discuss how the nature of professional misconduct can be quite variegated and nuanced, how boundaries between and within professions can be either too weak or too strong and lead to professional misconduct, and how the consequences of professional misconduct can be less straightforward than normally assumed. We also illuminate how some important questions about professional misconduct are still pending, including: how we define its different organizational forms; how it is instigated by the changing nature of professional boundaries; and how its consequences are responded to in professional organizations and society more widely.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.053
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.286
GPT teacher head0.521
Teacher spread0.235 · 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