Media, technologies de l’intellect, code numérique. De quelques implications du medium sur le social chez Innis, Goody et Herrenschmidt
Bibliographic record
Abstract
Cet article établit un dialogue entre l’œuvre de Jack Goody et celles de Harold Innis et Clarisse Herrenschmidt. Les concepts de modes de communication et de technologies de l’intellect élaborés par Goody sont d’abord confrontés aux développements consacrés aux media par Innis. Les catégories de savoir et de pouvoir sont analysées chez les deux auteurs à travers l’accent mis sur la culture lettrée par Goody et sur les monopoles du savoir par Innis. Les conséquences qui en sont tirées relativement à la production du social et aux processus cognitifs montrent tant des convergences que des différences, qui sont passées en revue. L’apport de Goody est ensuite passé au crible des travaux plus récents de Herrenschmidt qui, en pluralisant l’écriture (il est question des écritures) et en l’historicisant, fait émerger la question du code qui est au cœur de l’écriture informatique. Ce dialogue à trois par le biais de la figure médiatrice de Goody permet d’éclairer de manière originale les rapports entre media et société.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".