Bibliographic record
Abstract
We live in a society in which technical objects are omnipresent; where technology transforms our world and conceives its future shape. However, we are faced with a paradox which becomes more and more pressing. Technique influences us and we remain largely unaware of it. If we fail to conceive technique, then it is because we do not know how to do it. We have not learnt to apply Logos, or thought, or, more generally, science with regards to technique. Theoretical reflections on technique, on technology, the integration of technique or technology into the boundaries of science, have not occurred as a matter of course. Indeed, although archaic societies precluded invention, seeing technical objects as imitations of nature, Ancient Greek philosophy secularized technology, releasing it from the realm of magic and the divine to which it had been confined (Lamard, Lequin, 2006). In Aristotelian thought, the technical arts, which are a product of the metis, do not qualify as instruments of knowledge. The technical arts find themselves rejected from the Logos (Stiegler, 2004). They are not considered as an object of scientific knowledge. Consequently, in Metaphysics, Aristotle considers the technical arts to be intellectual activities with greater value than experience (a man of art knows the how and the why). Nevertheless, they have less value than science, hence making the technical arts a non-science. Finally, and as Sigaut (1994) pointed out, “technology is not what it should be because society does not yet consider the technical arts to be an interesting object of knowledge. And a science cannot exist if the object of that science is not legitimized by society”. By promoting works of the mind, the European Renaissance aroused renewed interest for technical art. During the Enlightenment, this interest was symbolized by the works such as
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.045 | 0.014 |
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".