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Record W2045154181 · doi:10.2308/bria.2001.13.1.111

A Research Note on the Effects of Gender and Task Complexity on an Audit Judgment

2001· article· en· W2045154181 on OpenAlex

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

VenueBehavioral Research in Accounting · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsYork University
Fundersnot available
KeywordsTask (project management)AuditPsychologyConsistency (knowledge bases)Social psychologyCognitionCognitive psychologyBalance (ability)Applied psychologyComputer scienceArtificial intelligenceAccountingEconomics

Abstract

fetched live from OpenAlex

This study examines the effects of gender and task complexity on the accuracy of audit judgments. Because research in cognitive psychology and marketing suggests that females may be more accurate decision makers in complex decision tasks, we hypothesize that there will be a significant interaction between gender and task complexity on the accuracy of an audit judgment. A 2×2 full factorial experiment (males/females by high-/low-task complexity) was carried out. The number and consistency of cues was manipulated to create the high- and low-complexity conditions. Participants were required to judge whether an inventory balance was fairly presented based on case material that contained a material misstatement in the inventory account balance. The results support the hypothesis.

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)0.033
metaresearch head score (Gemma)0.004
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 score0.892
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.653
GPT teacher head0.584
Teacher spread0.070 · 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