MétaCan
Menu
Back to cohort
Record W2282582929 · doi:10.5539/jel.v5n1p190

Ethics Training and Workplace Ethical Decisions of MBA Professionals

2016· article· en· W2282582929 on OpenAlexvenueno aff
Tamar S. Romious, Randall L. Thompson, Elizabeth Thompson

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyFeelingEthical issuesMedical educationEthical decisionPerceptionQualitative researchProfessional ethicsEngineering ethicsPedagogyPublic relationsSociologySocial psychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

<p>We recruited 15 MBA professionals in the St. Louis, Missouri metropolitan area to explore experiences and perceptions of classroom ethics training and ethical experiences in the workplace. Telephone interviews were conducted using open-ended questions to collect data that were uploaded to NVivo 10 for qualitative analysis. As a result of the data analysis, seven themes were recognized: (a) effective decision-making; (b) combining classroom instruction with real-world experience; (c) reasoning through an ethical issue; (d) resolution of workplace ethical issues; (e) feelings about ethics and corporate fraud; (f) fear of employer retaliation; and (g) expectations of management. One unexpected finding was that managers do not resolve ethical issues that the participants expect and that managers need more ethics training. The importance of human resources department was noted in dealing with ethical issues. A disturbing finding was the strong fear of retaliation for reporting an unethical issue. The self-assessment of the quality of ethics training in their MBA programs was mixed.</p>

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)0.015
metaresearch head score (Gemma)0.102
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.102
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.344
GPT teacher head0.520
Teacher spread0.176 · 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 designOther design
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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Education and LearningSame topicEthics in Business and EducationFrench-language works237,207