Bibliographic record
Abstract
Catherine Malabou’s conception of plasticity as potentially having a creative or destructive form provides both philosophy and the neurosciences with a dynamic and generative concept for describing the workings and transformations of psychological, social, and material phenomena. Exploring the dynamism of Malabou’s plasticity, I question: how is plasticity, whether as a giving or receiving form, constituted to be so dynamic? Drawing somewhat from Heidegger’s account of change, I propose thinking of form as existing within a world of forces, to be a force, and be composed of force(s). The problem being, though somewhat presupposed and even alluded to in her elaborations of form and destructive plasticity, Malabou doesn’t conceptualize force nor advance it as a necessity for conceptualizing plasticity. Nevertheless, developing upon Christopher Watkin’s idea for engaging Malabou’s plasticity relationally within a broader ecology, we come to see how, whether ontically or ontologically, force(s) appear to be what makes plasticity dynamic. As a result, in order to address the figure of force as being integral to form, I argue that Malabou will need to somehow transfigure her conception of plasticity. Ultimately, in my estimation, such elaboration may lead to plasticity’s conceptual re-birth in the form of a mediating force.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.063 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".