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Record W2105325767 · doi:10.1111/1911-3846.12046

Separating the Political and Technical: Accounting Standard‐Setting and Purification

2013· article· en· W2105325767 on OpenAlexvenueno aff
Joni J. Young

Bibliographic record

VenueContemporary Accounting Research · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingPoliticsFraming (construction)Accounting standardFinancial accountingPolitical scienceBusinessAccounting information systemEconomicsLawEngineering

Abstract

fetched live from OpenAlex

The U.S.‐based Financial Accounting Standards Board (FASB) emphasizes that accounting standard‐setting is not and should not be regarded as a “political process.” Employing the case of accounting for stock compensation, I examine a recent debate in which FASB appears to have successfully established and maintained a boundary between a technical accounting process and politics. This case is interesting because an earlier, failed effort to expense stock compensation was described as highly politicized. However, the boundary between technical and political processes was maintained in the more recent episode. I find that a focus on due process, characterizations of existing accounting requirements as anomalous and available measurement methods as reliable, and warnings about the dangers of injecting “politics” into standard‐setting were important to this boundary work. I also find that the boundary work required considerable interpretive flexibility in selecting (or ignoring) the evidence to be used in justifying the standard‐setting project and its conclusions. I conclude by suggesting that a different understanding of what it means to be involved in a “political process” might help all parties understand more fully what is taking place during the accounting standard‐setting process. Attention could be turned to developing processes to facilitate debates over which values should guide decisions occurring throughout the standard‐setting process. To this end, an enhanced standard‐setting process might allow for increased participation in agenda setting, in framing and scoping standard‐setting projects, and in providing opportunities for nonexperts to participate.

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 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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.001
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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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 teacher head, not a consensus.

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

Citations87
Published2013
Admission routes1
Has abstractyes

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