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Record W2038748204 · doi:10.1506/mm46-2226-7364-4750

Financial Times Business School Rankings: A Nontraditional Assurance Case in Three Parts*

2007· article· en· W2038748204 on OpenAlex
Andrea B. Davies, Steven E. Salterio

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueAccounting Perspectives · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsQueen's University
Fundersnot available
KeywordsNewspaperAudience measurementPublicationRanking (information retrieval)Position (finance)BusinessFinanceExecutive educationPolitical scienceAccountingBusiness modelMarketingAdvertisingElectronic businessComputer science

Abstract

fetched live from OpenAlex

ABSTRACT The Financial Times of London (FT) is a business newspaper, with daily editions published in the United Kingdom, continental Europe, the United States, and Asia, and an estimated daily readership of 10 million people. In 1999 the FT began to publish a ranking of what it considered to be the top business schools in the world. Since their inception, these rankings have become increasingly relied upon by potential students and business school administrators worldwide. The FT's ranking is unique compared with other rankings because of its special international focus. Given the prominence of these rankings and the FT's position as a well‐respected business newspaper, the question of providing assurance over the business school rankings that the FT provides is particularly challenging.

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)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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