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Record W2011880482 · doi:10.1111/1099-1123.00309

Quality Audit in Financial Investment Services

2000· article· en· W2011880482 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Auditing · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsUniversity of ManitobaDalhousie University
Fundersnot available
KeywordsAuditQuality auditBusinessAccountingQuality assuranceQuality (philosophy)Investment (military)Audit planService (business)Service providerJoint auditFinanceInternal auditMarketing

Abstract

fetched live from OpenAlex

This paper discusses the following two questions: What is a ‘Quality Audit’? Why and how does it apply to financial investment services? ‘Quality’ in this important field of service is understood as the perception of the investor about achieving satisfactory returns, under generally accepted risks, within a planned time. The service provider normally assures this quality with due care mostly in information gathering, communication and investment decision‐making. Once this quality assurance is adequately formalized and documented, a ‘quality audit’ can be performed. The ISO 9000 international standards and guidelines describe a quality system that can be applied to provide meaningful quality assurance in investment services. Respective quality audits are described in the ISO 10011 Quality Audit Guideline. The development of quality assurance systems and quality audits for compliance and improved performance presents benefits to both the client and the investment service provider.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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