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Record W2518155849 · doi:10.1111/1911-3846.12277

The Impotence of Accountability: The Relationship Between Greater Transparency and Corporate Reform

2016· article· en· W2518155849 on OpenAlexaffvenue
Vaughan S. Radcliffe, Crawford Spence, Mitchell Stein

Bibliographic record

VenueContemporary Accounting Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsWestern University
Fundersnot available
KeywordsCorporationPublicityAccountabilityRealmCorporate governanceAccountingTransparency (behavior)Political sciencePublic administrationBusinessEconomicsManagementLaw

Abstract

fetched live from OpenAlex

Abstract This paper explores the role of accounting in the attempted reform of the corporation during the “progressive era” in the United States. Focusing on the activities of three institutional bodies in the early twentieth century, the paper documents how their repeated recourse to “publicity,” which relied crucially on accounting technologies, failed to turn the corporation into an entity more sensitive to the public interest. Specifically, two interrelated contributions are made to existing literature on accounting and corporate governance. Firstly, the paper documents the early historical development of the now taken‐for‐granted phenomenon of accounting and adjudicating at the entity level (Miller and Power 2013). Secondly, the paper offers a rejoinder to present‐day projects of corporate governance which identify better and enhanced accountability as key to the successful reform of the corporation. During the progressive era, accounting expanded and territorialized new spaces, bringing trusts out of a hitherto secretive, private realm and into the view of the public. Yet this was not enough to engender substantive corporate reform.

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)0.025
metaresearch head score (Gemma)0.085
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 score0.025
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.045
Scholarly communication0.0090.010
Open science0.0010.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.180
GPT teacher head0.319
Teacher spread0.139 · 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

Citations34
Published2016
Admission routes2
Has abstractyes

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