Mauro Carbone et GrazianoLingua, Towards an Anthropology of Screens: Showing and Hiding, Exposing and Protecting, Palgrave Macmillan, 2023
Bibliographic record
Abstract
L’ouvrage de Mauro Carbone et Graziano Lingua propose une anthropologie des expériences écraniques. À la suite de la pandémie de la COVID-19, ils proposent de repenser la nature et le statut des écrans, et avec eux la philosophie. Grâce à une grande érudition interdisciplinaire, les auteurs subvertissent les réflexions actuelles sur les écrans qui présupposent une métaphysique platonicienne implicite qui les réduit à une simple surface, alors qu’ils sont des dispositifs relationnels qui montrent et cachent, exposent et protègent. Adoptant un point de vue transhistorique, ils voient le corps comme un proto-écran, origine de la notion d’archi-écran. Celle-ci permet tout à la fois de rendre compte de la variété historique et technique des écrans qui constituent toujours déjà la culture humaine, ainsi que de remettre en cause les catégories traditionnelles de la philosophie issues de cette métaphysique.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".