MétaCan
Menu
Back to cohort
Record W3125868777

Worldscope meets Compustat: A Comparison of Financial Databases

2005· preprint· en· W3125868777 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueRePEc: Research Papers in Economics · 2005
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsDatabaseAccountingQuality (philosophy)Outcome (game theory)Actuarial scienceData sourceFinanceBusinessEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

With this study we are the first to systematically compare today’s two major counterparts as a source of accounting and financial data for researchers: Compustat North America by Standard & Poor’s and Worldscope by Thomson Financial. This investigation is conducted for U.S. and partly Canadian data over an extensive period from 1985 to 2003. We examine more than 650 data items available in both databases and address the question of whether or not the decision for one or the other source may have an impact on the outcome of research projects. It is probably commonly assumed that this impact is minor, but it also leaves room to question certain results. We show that the use of both databases should lead to comparable results, but also find that if, e.g. a size bias, is not treated with care the quality of results may differ considerable. Furthermore after 1998 the number of firms covered by Worldscope exceeds the one covered by Compustat by about one fourth.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.002
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 head0.119
GPT teacher head0.396
Teacher spread0.278 · 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