Bibliographic record
Abstract
Anyone Who Likes Cats and Dogs Is a FoolAsking whether humans can be friends with animals is fraught.So many people have such intense relationships with animals, perhaps most especially their pets, that hazarding that question is affectively perilous and something of a philosophical watershed.Tread lightly, or inevitably someone who is BFFs with their budgie will cancel you for your callousness.When Deleuze and Guattari dropped "Anyone who likes cats and dogs is a fool" and then returned and developed the argument recursively throughout A Thousand Plateaus, they were in part trying to argue that owning a pet distances and bulwarks humans from their own animality.They were longing to relate to a cat as animal-to-animal, not as human-to-animal, and in the process recover something of their own animality.There are many salient points of critique of the Deleuze-Guattari desire for becoming-animal, depths that Donna Harraway has famously plumbed.Among them is the strangeness of claiming that a pet is an animal, when they have so patently entered into a different, hybrid, maybe becoming-human zone.The question for us here is whether friendship is a mode of relationship that offers any interspecies traction: or, can we be friends with any more-than-humans?And if so, how would we know?The proposition that humans and more-than-humans might relate to one another as friends rests on acknowledging that pets, animals, plants, rivers, mountains and all the rest have active subjectivities, and might be willing to consider an offer of friendship.We suggest that all of us, human and more-than, are constantly shaping and reshaping our
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.020 |
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".