Bibliographic record
Abstract
Hubka's theory of technical systems (TTS) is briefly outlined. It describes commonalities in all engineering devices, whatever their physical principles of action. This theory is based on a general transformation system (TrfS), which can be used to show engineering in the contexts of society, economics and historic developments. The life cycle of technical systems consists of seven major TrfS, each consisting of further product-specific TrfS. From this TTS, Hubka derived a methodology as voluntary guide to systematic design engineering, for application when an intuitive approach based on experience proves to be ineffective. This approach to engineering design is distinct from more artistic designing. The methodology applies to novel design problems, and to re-design. Some educational aspects are developed to show the range of knowledge needed for engineering designing. Operators of a TrfS are also TrfS – illustrated by observing the management systems in the TS-life cycle. Connections to the general economy, and its financial consequences, are shown on TS-life cycle LC4 with its supply chain, and on LC6 and LC6A, with the need to service the operating product, and to establish supply and distribution chains. Transformation systems are hierarchical, each TrfS is a sub-system to a more complex system – each sub-system can be viewed as a TrfS, leading to a repeating use of the same design methodology for sub-systems. Invention and innovation in TrfS can be shown (historically) to alter the state of society, beneficially and adversely. A comparison with a different methodology is mentioned.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".