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Record W1590206522 · doi:10.1108/09513570210425600

A literary theory perspective on accounting

2002· article· en· W1590206522 on OpenAlexaff
Norman B. Macintosh, C. Richard Baker

Bibliographic record

VenueAccounting Auditing & Accountability Journal · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsEpistemologyLiterary criticismSociologySemioticsContext (archaeology)Literary sciencePerspective (graphical)Literary theoryMeaning (existential)Structuralism (philosophy of science)CriticismRealismLinguisticsAccountingLiteraturePhilosophyHistoryArtEconomics

Abstract

fetched live from OpenAlex

This paper adopts a literary theory perspective to depict accounting reports and information as texts rather than as economic commodities and so available for analysis from the vantage point of semiotic linguistic theory. In doing so it takes the literary turn followed by many of the social sciences and humanities in recent decades. It compares and contrasts four dominant genres of literary theory – expressive realism, the new criticism, structuralism, and deconstructionism – to developments in accounting. The paper illustrates these and other ideas in the context of the controversies surrounding the oil and gas accounting crisis and practices circa 1961 to 1990. The paper concludes by outlining a new way of preparing accounting reports based on Mikhail Bakhtin’s notion of the heteroglossic novel. This approach calls for making accounting for an enterprise an ongoing conversation rather than a monologic process of closing down on a single meaning.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.004
Science and technology studies0.0060.034
Scholarly communication0.0140.013
Open science0.0020.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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 designTheoretical or conceptual
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

Citations74
Published2002
Admission routes1
Has abstractyes

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