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Applying XBRL in an Accounting Information System Design Using the REA Approach: An Instructional Case*

2010· article· en· W1567391107 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAccounting Perspectives · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and XBRL
Canadian institutionsnot available
Fundersnot available
KeywordsXBRLComputer scienceAccounting information systemRelational databaseDatabaseAccountingBusiness reportingProcess (computing)Financial accountingWorld Wide WebBusinessProgramming language

Abstract

fetched live from OpenAlex

Abstract The Church in Somewhere (CIS) is a small community church which uses an Excel spreadsheet to keep its financial records. The church administrator is considering moving from a spreadsheet accounting system to a relational database system that can easily be expanded to include more information in the future. In this paper we examine the transforming process in this hypothetical case by following a resource‐event‐agent (REA) modeling paradigm to create a database. We then link the REA model to financial reporting using Microsoft Access. In addition, using the financial report in the database, students prepare and validate an eXtensible Business Reporting Language (XBRL) document for CIS. Instead of applying the complex U.S. Generally Accepted Accounting Principles (GAAP) Taxonomies, Release 2009 , the case uses a dedicated CIS Taxonomy to complete the mapping and tagging processes.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.010
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 head0.034
GPT teacher head0.253
Teacher spread0.219 · 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