Bibliographic record
Abstract
This text has several pre-texts.It is the continuation of a dialogue between several writings, and its aim is to try to grasp the significance of these writings and of their enunciatory functions and, above all, the relationship between them.It will be necessary, first of all, to give an overview, or rather a brief schematization, of this network of texts.It would, of course, be impossible to give an exhaustive account of all the textual relationships that weave the fabric of this discourse, for the cross-references, presuppositions, sources of inspiration, repetitions, and pastiches are too numerous-even if theoretically finite. 1 This text chooses a precise point as the centre of its analysis and looks at the emergence of the network from this centre.The centre is the interaction-or, as will be proposed later following the proposal of another text (Barad), the intra-action-between two texts: The Writer is the Architect.Editorialization and the Production of Digital Space (Vitali-Rosati) (from now on: WA) and If One has the Floor, does One also need to Dance?Topology, Choreology, and the Structure of Digital Space (Vučković) (from now on: OFOD). 2 From this center, the network will be followed in a group of other texts that are also signed with the name Marcello Vitali-Rosati (from now on: MVR)-in part cited by OFOD.This group of texts will serve here to try to answer the question: "who is the writer?"Or, in this specific case: "who is MVR?"
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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".