Audit and self‐assessment in quality management: comparison and compatibility
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.
Bibliographic record
Abstract
In recent years, two performance evaluation methodologies have received significant attention in managerial circles: quality audit and self‐assessment. While the quality audit examines the compliance of a quality system with ISO 9000 standards and its suitability to achieve stated objectives, the self‐assessment measures organizational performance against a selected business excellence model. In a continuous improvement effort, an organization can lay out the groundwork by establishing an ISO 9000 quality system, and subsequently use an excellence model to enhance performance, thereby effectively applying both evaluation methodologies. This paper compares the principles and practices of quality audits and self‐assessments, for the purpose of examining their compatibility and providing the basis for integration. Numerous differences in the concepts, purpose, scope and methodology are illustrated, and self‐assessments are found to be more advantageous in enabling continuous improvement. However, it is concluded that audits and self‐assessments are compatible, and further research into the issues of enhancing both methodologies is suggested.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it