The Need for a Biopolitics of Scientific Discourses on Emotion and Affect
Bibliographic record
Abstract
Reading Professor Leys’s work — and having heard her series of lectures on this project some years ago at the University of Toronto — has provided a rich opportunity to re-immerse myself in debates within and across the humanities and sciences. Her careful and intensive work in this area — a project in which she has been deeply absorbed for many years — opens up crucial questions about the nature of emotions and what we can know about them. It has been inordinately challenging to choose where best to focus a short response. Leys’s argument is best understood by supplementing this reading with her criticism of “new affect theorists” and the ensuing contested published debates in the journal Critical Inquiry. Leys’s rigorous and critical scholarship investigates how the neuroscientific repackaging of Darwin’s Basic Emotions View continues to dominate our conceptualizations and theorizations of emotion in Western culture, both across the humanities and sciences as well as in popular thought. Her reasons for developing this critique reflect her hope — one shared by many since the beginning of written records of the human struggle to understand emotions — that we might develop an understanding and even a science of emotions that does not reinscribe dualisms between emotion and cognition. Clearly refusing touchy-feely, overly speculative, sloppy, or empty theorizing, Leys seeks an account that understands the processes of emotion, affect, cognition, and behavior — from whatever disciplinary perspective — as a phenomenon situated in the “whole person,” not in a Cartesian version of self, not in a self animated solely by instinct. Joining with others in this search, her work invites us to examine more carefully how and when affect theorists do or don’t succumb to the binaries that serve dominant Western cultural paradigms rooted in longstanding oppositions such as emotion/reason, body/mind, and so on.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.008 | 0.100 |
| Scholarly communication | 0.020 | 0.026 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.016 |
| 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".