Bibliographic record
Abstract
The paper questions the postmodern, wide-spread tendency to abusively reconstruct the meaning of some texts of the philosophers of the past, so that they may serve as allies or foes in our own contemporary ideological wars. The chosen example is an article by Umberto Eco, called “Anti-Porphyry”, and the parallel chapter, “Dictionary vs. Encyclopedia”, from his well-known book Semiotics and the Philosophy of Language. According to Eco, the famous “Porphyry’s tree” is the pictorial representation of the so-called “strong thought”, which — so he believes — was being subverted from the outset in the benefit of the “weak thought” or “Encyclopedia thought” even in the works of some essentialist philosophers like Aristotle or St. Thomas Aquinas. On the other hand, Eco thinks he found in d’Alembert’s Discours préliminaire to the French Encyclopédie a forerunner of postmodern “weak thought”, which resembles the so-called 3rd type labyrinth or the “rhizome” described by G. Deleuze, and which is the opposite of the logic encapsulated in the “Porphyry tree”. The paper attempts to show that Eco distorted the ideas of the above-mentioned philosophers by dislodging them from their original metaphysical context and by manipulating some of the relevant texts. So, in Eco’s view, both Aquinas and d’Alembert anachronistically became forerunners of postmodernism. In fact, what Eco eventually got was less an accurate description of some philosophies of the past, than a historical-philosophical reconstruction rather abusively legitimizing his own ideas.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".