Some thoughts on quality models: evolution and perspectives
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
<p>‘Quality’ is an evolving concept, quite difficult to be defined, whatever the application domain observed. As Tom Demarco said, it’s true that “you cannot control what you cannot measureâ€. But coming back, it’s also true that “you cannot measure what you cannot define†and again “you cannot define what you don’t knowâ€. Thus, moving from a common, shared definition is the priority for any activity and creates also measures from any measurement and benchmarking activity. Along the years, several ‘quality models’ (QM) have been produced: the <em>scope</em> for non-functional attributes (part of the ‘quality’ definition, also according to ISO) is enlarging. This paper discusses the evolution of the quality concept (broader than the one referred to the solely ‘product’) in order to observe which perspectives can be drawn up for the next years.</p>
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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