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Record W1647381466 · doi:10.19030/iber.v1i12.4007

Evidence Of Method Effects In Budget-Related Behavior Research

2011· article· en· W1647381466 on OpenAlexaff
Alfred E. Seaman, John Joseph Williams

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)EconometricsStructural equation modelingPsychologyResponse biasTest (biology)Survey researchApplied psychologyComputer scienceSocial psychologyEconomicsMachine learningGeography

Abstract

fetched live from OpenAlex

Research has revealed numerous budget-related behavior (BRB) dimensions that describe managers actions and interactions with their budgetary control systems. This research has been conducted using a survey questionnaire methodology. However, those responding to the questionnaires may do so on a basis other than the specific item content. This paper uses a structural equation approach to investigate systematic response bias in BRB survey type research. Data from Singaporean companies is used to test for the presence of response bias and results confirm this expectation. The implication is that future studies in this context should investigate the structure and potential impact of response bias.

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)0.421
metaresearch head score (Gemma)0.669
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.714

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4210.669
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.006
Science and technology studies0.0030.007
Scholarly communication0.0060.005
Open science0.0030.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.251
GPT teacher head0.404
Teacher spread0.153 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations3
Published2011
Admission routes1
Has abstractyes

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