Hypes, hopes and actualities: new digital Cartesianism and bodies in cyberspace
Bibliographic record
Abstract
‘New Digital Cartesianism’ investigates the socio-material power inequities embedded in text-based, computer-mediated communication (CMC). Is the body really transcended in text-based computer-mediated communication? This article summarizes software and hardware advertising ‘hypes’, cyber-enthusiast ‘hopes’, and the ‘actualities’ of CMC which contradict this virtual dream of pure minds communicating. Marketing hypes and cyberhopes mythologize disembodied CMC with promises of anonymity and fluid identities. However, the actualities of how users interpret and derive meaning from text-based communication often involve reductive bodily markers that re-invoke stereotypes of racialized, sexualized and gendered bodies. Ironically, despite claims that CMC achieves Descartes’ dream of ‘pure minds’ and the transcendence of body, users frequently rely on stereotyped images and descriptions of bodies in order to confer authenticity and signification to textual utterances. In digital Cartesianism, the body actually functions as a necessary arbiter of meaning and final signifier of what is accepted as ‘real’ and ‘true’.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.080 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".