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A Case of Academic Misconduct: Does Self‐Interest Rule?*

2011· article· en· W2333077217 on OpenAlexaffvenue
Joanne Jones, Gary Spraakman

Bibliographic record

VenueAccounting Perspectives · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsYork University
Fundersnot available
KeywordsMisconductRationalization (economics)Academic integrityContext (archaeology)Scientific misconductPublic relationsPsychologyAccountingPolitical scienceSocial psychologyBusinessLawMedicine

Abstract

fetched live from OpenAlex

Abstract Most analyses of academic misconduct focus on students’ integrity and what is taught at the universities. Surprisingly little attention is paid to the role of faculty members. This article presents an unusual case of academic misconduct that provides an opportunity to examine the actions and rationalizations of the students and faculty members involved in the event as well as the broader university context. The case is unusual in that the instructor initiated and facilitated the academic misconduct. The analysis of the misconduct and the subsequent events suggest that self‐interest rules and concerns for wider interests are all but silent. While the case presents a somewhat dismal view of the integrity of some accounting faculty members and future accountants, it provides interesting insight into self‐interest, rationalization, social context, and both students’ and faculty members’ integrity. The analysis discusses the mechanisms used to prevent and manage faculty member misconduct, along with limitations of self‐regulation and student reports as forms of control. The article also considers how accounting educators can encourage future accountants to act with integrity and concludes that in order to achieve that goal, accounting educators must serve as role models who act honestly.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.328
Teacher spread0.268 · 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.

Study designQualitative
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

Citations7
Published2011
Admission routes2
Has abstractyes

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