MétaCan
Menu
Back to cohort

"Stigma and Legitimacy Loss: Professions, Social Judgments, and Symbols in Crime and Punishment"

2016· article· en· W2800862967 on OpenAlexaffabout
Donald Palmer, Aharon Cohen Mohliver, Timothy R. Hannigan, Jacob Model, Celia Moore, Ivana Naumovska, Joseph F. Porac, James B. Wade, Georg Wernicke

Bibliographic record

VenueAcademy of Management Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Educational Sciences
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMisconductSeriousnessCorporate governanceWhite-collar crimeApportionmentCriminologyLegitimacyPolitical sciencePsychologySociologySocial psychologyPublic relationsLawManagementPolitics

Abstract

fetched live from OpenAlex

In this symposium we present five papers focused on how the judgments of external stakeholders affect the apportionment of the consequences of misconduct. The papers included attack the question in various settings and across levels of analysis, ranging from teachers’ personal comportment to members’ of Parliament misspending to corporate fraud. Yet each paper investigates how social control agents - including the media, institutional investors, stock analysts, and other audiences - draw inferences about the seriousness and severity of infractions, and how these inferences affect the punishments that are assigned to various actors involved. This symposium will generate conversation about both theoretical and empirical questions related to misconduct and ethics, stakeholder relationships, and governance. Pragmatic or Moral Legitimacy: Effect of Director Capabilities versus Nonprofit Ties on Punishment Presenter: Daphne Teh; INSEAD Repeat Offenders: How The Consequences of Firm Misconduct Abate Across Incidents Presenter: Celia Moore; London Business School Presenter: Aharon Yehuda Cohen Mohliver; London Business School Presenter: Jo-Ellen Pozner; Santa Clara U. The Process of Scandal Formation and the Role of Social Control Agents Presenter: Timothy R. Hannigan; U. of Alberta Presenter: James B. Wade; George Washington U. Presenter: Joseph Porac; New York U. The Professional Consequences of Misconduct Presenter: Jacob Model; Stanford U. Corporate Misconduct and Heterogeneity in the Reputational Penalties to Managers and Directors Presenter: Ivana Naumovska; INSEAD Presenter: Georg Wernicke; Copenhagen Business School

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.376

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 communication0.0000.001
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 head0.040
GPT teacher head0.350
Teacher spread0.309 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicSocial and Educational SciencesFrench-language works237,207