Turner Boxes and Bees: From Ambivalence to Diffraction
Bibliographic record
Abstract
This paper is a Research through Design (RtD) investigation that deeply reflects on our ambivalence with three design choices we made while designing in a multispecies context. The ongoing RtD project, called Turner Boxes, aims to design a technological network to interact with wild bees in an urban environment. The design choices negotiate challenges we encountered, including the potential effects of electromagnetic fields (EMF) on bee ecologies; sucrose feeding as an established human-bee interaction; and the question of human intervention when designing in relation to other species. We analyze our negotiations of these challenges along with the practices of beekeepers and ecologists who were part of our investigation, to realize that ambivalence is a characteristic and a resource in multispecies designing. We extend this analysis through feminist epistemologies to articulate a position of diffraction, a standpoint from which to design in multispecies worlds in which interdependencies and differences are critical.
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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 | 0.035 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.078 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".