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Record W1982870854 · doi:10.1108/02656710610672470

A review of research on cost of quality models and best practices

2006· review· en· W1982870854 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 Quality & Reliability Management · 2006
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsQuality (philosophy)Quality costsActivity-based costingOrder (exchange)Computer scienceManagement scienceRisk analysis (engineering)Quality managementOriginalityProcess managementOperations managementEngineeringBusinessMarketingQualitative researchManagement system

Abstract

fetched live from OpenAlex

Purpose This paper aims to present a survey of published literature about various quality costing approaches and reports of their success in order to provide a better understanding of cost of quality (CoQ) methods. Design/methodology/approach The paper's approach is a literature review and discussion of the issues surrounding quality costing approaches. Findings Even though the literature review shows an interest by the academic community, a CoQ approach is not utilized in most quality management programs. The evidence presented shows that companies that do adopt CoQ methods are successful in reducing quality costs and improving quality for their customers. The survey shows that the method most commonly implemented is the classical prevention‐appraisal‐failure model; however, other quality cost models are used with success as well. Originality/value The paper shows that the selected CoQ model must suit the situation, the environment, the purpose and the needs of the company in order to have a chance to become a successful systematic tool in a quality management program.

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)0.034
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.400
GPT teacher head0.533
Teacher spread0.134 · 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