THE POLITICS OF BECOMING: BREAKING THE IDENTITY GROUND OF CYBORGS/POSTHUMANS AND HUMANS
Bibliographic record
Abstract
Although the fixity of identity constitutes a basis for theory in Identity Politics, the debate on identity as pre-political seems to find its limits when confronted with discourses in feminism, technology and ecological thought. This paper will explore a vision of identity that enhances the way we penetrate political conflicts, by exploring visions of humanity inspired by science fiction (SF). I believe that exploring figures and creatures in Fiction/SF makes it possible to interrogate theoretical categories of identity; that is, these forms of art enhance our imagination, contest boundaries/categories, transform our understanding and perceptions of theworld/realities/subjectivities, and, more specifically, foster how we enter and conceptualize political conflicts and concepts. In this piece, my aim is to consider illustrationsof humanness as depicted in Mamoru Oshii’s film Ghost in the shell (1995). Indeed, SF problematizes and embraces a dynamic vision of humanity where body and mind are intermeshed. Moreover, when technology stains our conception of a pure humanity – destroying the human capacity to reproduce and to die – we shall see that the protagonist in Ghost in the shell (Heretofore Ghosts) seems to discover the potential to mingle both cyborgs/technology and humanness.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.046 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.002 | 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".