Bibliographic record
Abstract
In the context of the highly contested discourse of posthumanism, this essay examines Mark Hansen’s attempt to give a robust account of technology in its extra-linguistic dimension by evincing an ‘‘‘originary’’ coupling of the human and the technical’ that grounds experience as such (Hansen, 2006a: 9). Specifically, I argue that Hansen’s perspective is haunted by the representational logic that it moves against. In this, I do not repudiate Hansen’s argument as such, but rather reject one of its central underlying implications: that the extra-discursive materiality of technology might be accessed, linguistically, without attaching a meaning to it that is foreign to this materiality. To this end, the essay begins with an examination of technesis as it is initially developed by Hansen, demonstrating the necessity from which it sprang, the contribution that Hansen’s reading makes, and its ultimate limitations. From here, the essay articulates Hansen’s argument for an affective topology of the senses, corroborating the increased importance of digital technologies in this perspective through a brief comparison of Roberto Lazzarini’s ‘skulls’ (as read by Hansen) and my own piece ‘Sound’. Finally, this comparison pivots the essay towards a critical analysis of Hansen’s account of primary tactility that demonstrates its dependence on the (representational) logic of language. In closing, then, I argue that what is accomplished by Hansen’s putting-into-discourse of technesis is, paradoxically, a re-staging of the constitutive ambivalence of deconstruction that reinvigorates the posthumanist elements of that discourse.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".