Relationality and Metaphor—Doctrine of Signatures, Ecosemiosis, and Interspecies Communication
Bibliographic record
Abstract
The Doctrine of Signatures (DoS) figures prominently in both contemporary and historic herbal traditions across a diversity of cultures. DoS—conceptualized beyond its conventional interpretation as “like cures like”, which relies solely on plant morphology—can be viewed as a type of ecosemiotic communication system. This nuanced form of interspecies communication relies on the presence of “signatures”, or signs, corresponding to the therapeutic quality of different plants based on their morphology but also their aroma, taste, texture, and even their context in the landscape. Despite its widespread contemporary dismissal by mainstream science as overly simplistic, childlike, primitive, and generally of limited value, we suggest that the recognition of “signatures” in plants may be considered as a form of communication between humans and plants. Drawing upon Indigenous thought, ecosemiotic theory, and lyric philosophy, we posit that understanding “signatures” metaphorically, as a reflection of the “shape of the world”, offers insights into the interconnectedness of all life forms—a profound affirmation of relational coherence between humans and the more-than-human. We advocate for another perspective on DoS: one which holds potential towards reorienting and restoring our relationships in the vibrant world of the Anthropocene.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.045 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".