Poetic Inquiry as Minor Research: A New Direction in Humanities' Methodologies of Research
Bibliographic record
Abstract
This paper introduces poetic inquiry as minor research and positions poetic inquiry not in opposition to major forms of research in the social sciences and humanities but as transforming and deterritorializing in relationship (Deleuze and Guattari, 1986, 1987). Where, unlike discursive-narrative forms of research, poetic inquiry is not defined by the hegemonic power (pouvoir) of constraints of description, argument, analyses and interpretation, as an onto-epistemological activity, but by the contagious power (puissance) of the variations of responsiveness as an ethical act or performance (Deleuze and Guattari). Stretching tensors all throughout, in ever-new direction of continuous variation, the inquiry makes the research itself stammer, introducing a line of departure or flight to dominant territories of epistemology or assemblages of a thousand plateaus of narrative-discourse. In this way, poetic inquiry transforms the inquiry itself into something else: it is the possibility of an event of responsiveness. Poetic inquiry as a research methodology introduces the emergence of a system of openness (Massumi,2002) and creative contagion within a research genre that may perform nothing more than the act of ethically responding to the call of an other.
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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 | 0.068 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.008 | 0.170 |
| Scholarly communication | 0.027 | 0.039 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".