Bibliographic record
Abstract
Dans la série X-Files, la réalité est pensée, de manière lacanienne, comme une surabondance illusoire (paradoxa-lement d’une grande pauvreté) et comme un leurre, que crée et vectorise le langage et qu’intensifie le désir de croire aux témoignages de nos sens. Or, parce que le personnage de Mulder cherche à nommer ce réel, il le manque et est voué dès lors à une « passion des semblants », envers de la « passion du réel » définie par Zizek. C’est dès lors la série — par son inachèvement et ses ellipses — qui prendra en charge cette rétivité foncière du réel à la nomination.AbstractReality is, in the series X-Files, thought in a Lacanian manner, as an illusory abundance (paradoxically, of a great poverty) and as a decoy created and vectorized by language and intensified by the desire to believe the testimony of our senses. However, because the character of Mulder tries to name the “real”, he misses it and is therefore doomed to a “passion of semblance”, opposite of the “real passion” defined by Zizek. It is therefore the series — through its incompleteness and ellipses — that will confront this resistance of the “real” to denomination.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.069 | 0.020 |
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".