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Record W3209803486 · doi:10.33423/jabe.v22i7.3249

Factors Associated With Student Performance in Graduate Managerial Accounting: An Empirical Study at a US Commuter Public University

2020· article· en· W3209803486 on OpenAlexvenueno aff
Mostafa M. Maksy, Myung-Ho Yoon

Bibliographic record

VenueJournal of Applied Business and Economics · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingPsychologyGraduate studentsPublic universityMedical educationWork (physics)BusinessPedagogyPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

The grade the student intends to earn in the course, and intention to take the CPA or the CMA exam are strong motivating factors for the students to perform well in the Graduate Managerial Accounting (GMA) course. The number of work hours, job type, and course load do not have any negative effect on student performance. Communication skills are significantly associated with student performance. The grade in the Accounting for Managers course and overall GPA are strong predictors of student performance in the GMA course. Neither age nor gender has any effect on student performance. Finally, the undergraduate major has a significant effect on student performance with the undergraduate accounting major taking the first place in leading to the best performance, followed by finance, other non-business major (surprisingly), with management and marketing tied for fourth place.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.066
GPT teacher head0.237
Teacher spread0.171 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2020
Admission routes1
Has abstractyes

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