Bibliographic record
Abstract
Abstract Brian Massumi (1956–) is a contemporary political theorist of communication, critical and cultural studies, philosophy, political theory, science, and aesthetics. One of the foremost thinkers of “radical empiricism,” he is responsible for enabling the widespread use of Deleuzean philosophy in communication and inaugurating the so-called “affective turn” in the theoretical humanities. Massumi is Professor of Communication at the Université de Montréal and a collaborator with the experimental art and activism lab SenseLab, founded by Erin Manning. His most well-known translation is Gilles Deleuze and Felix Guattari’s A Thousand Plateaus (1987), and he is the author of ten books, including the widely influential Parables for the Virtual: Movement, Affect, Sensation (2002). Massumi’s radical empiricist approaches concern the aesthetics of communication and power in the context of global capitalism. He opens the field of communication to the study of relationality, what he calls “being-in-becoming,” which he describes in terms of Gilles Deleuze’s “the actual” and “the virtual.” His critical embrace of becoming reframes the concept of “the event” as a processual unfolding of forces of expression, or experience. Instead of remaining wedded to communication models that limit language to designation, manifestation, and signification, Massumi’s focus on becoming calls for accounts of the extra-linguistic. Three key concepts include expression, affect, and perception. Through creative and experimental dispositions, Massumi position the fields of communication, critical and cultural studies, philosophy, political theory, science, and aesthetics toward vibrant scenes of relations-already-underway, or how feeling, thinking, and being begin, again, in the middle of something already underway—a “happening doing.”
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".