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Record W3194197318 · doi:10.1017/s0959774321000421

Everyday Knowledge and Apothecary Craft: Pharmacopoeias of Ancient Northwestern Honduras

2021· article· en· W3194197318 on OpenAlexaff
Shanti Morell‐Hart

Bibliographic record

VenueCambridge Archaeological Journal · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsApothecaryPharmacopoeiaEthnobotanyCraftEthnographyGeographyApprenticeshipDomesticationHistoryTraditional medicineEthnologyAnthropologyArchaeologyAncient historyMedicinal plantsSociologyMedicineBiologyClassicsAlternative medicineEcology

Abstract

fetched live from OpenAlex

Medicinal practices were critical in ancient societies, yet we have limited insight into these practices outside references found in ancient texts. Meanwhile, historic and ethnographic resources have documented how a number of plants, from across the landscape, are assembled into pharmacopoeias and transformed intomateria medica. These documentary resources attest to diverse healthcare practices that incorporate botanical elements, while residues in the archaeological record (seeds, phytoliths and starch grains) point to a variety of activities, some of them therapeutic in nature. Focusing on four pre-Hispanic communities in northwestern Honduras, I draw upon ethnobotanical and ethnobiological knowledge to infer medical practices potentially represented by ancient plant residues. Comparing these findings with prior investigations, I address the limits of dividing taxa into mutually exclusive categories such as ‘food’, ‘fuel’ and ‘medicine’. I consider the importance of apothecary craft in past lifeways, as well as the persistence of many traditions in contemporary medical practice.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.032
GPT teacher head0.264
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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