Bibliographic record
Abstract
The following paper provides a critical and storied account of how my literal and literary encounters with Eastern Tent Caterpillars invites me to re-encounter space as a concept and a living reality that shapes my research, my perception of myself as a researcher, and my perception of myself as a body. More specifically, observing caterpillars’ spatial relations challenges me to embrace space(s) as lively and packed with non-uniform potentials for world-building; accepting space as alive demands that the body-in-space (in my case, a white, settler, woman, and former anorexic body) be marked as a non-neutral world-building agent alongside other spatial bodies. This paper ponders some of the discomforts, tensions, and promises of embracing embodied research as an always-creative and potentially intrusive spatial act, and it explains how my research has helped me shift my focus from how much space my body inhibits—where less is always good, more is always bad— to what relationships I am building through and in my embodied research.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.035 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".