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Record W4390841210 · doi:10.1002/ppp3.10468

Orphan crops of archaeology‐based crop history research

2024· article· en· W4390841210 on OpenAlexfundno aff
Daniel Fuks, Frijda Schmidt, Maite Iris García Collado, Margot Besseiche, Neal Payne, Giovanna Bosi, Charlène Bouchaud, Elisabetta Castiglioni, Vladimir Dabrowski, Suembikya Frumin, Dorian Q. Fuller, Roman Hovsepyan, Sureshkumar Muthukumaran, Leonor Peña‐Chocarro, Guillem Pérez Jordà, Jérôme Ros, Mauro Rottoli, Philippa Ryan, Robert N. Spengler, Chris J. Stevens, Soultana-Maria Valamoti, Ehud Weiss, Michelle Alexander, Muriel Gros‐Balthazard

Bibliographic record

VenuePlants People Planet · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaHorizon 2020 Framework ProgrammeMinisterio de Ciencia e InnovaciónUniversity of CambridgeHezkuntza, Hizkuntza Politika Eta Kultura Saila, Eusko Jaurlaritza
KeywordsAgricultural biodiversityRepresentativeness heuristicAgricultureAgroforestryContext (archaeology)BiodiversityCropGeographyPaleoethnobotanyBiologyEcologyArchaeology

Abstract

fetched live from OpenAlex

Societal Impact Statement Agrobiodiversity is central to sustainable farming worldwide. Cultivation, conservation and reintroduction of diverse plant species, including ‘forgotten’ and ‘underutilized’ crops, contribute to global agrobiodiversity, living ecosystems and sustainable food production. Such efforts benefit from traditional and historical knowledge of crop plants' evolutionary and cultural trajectories. This review is a first attempt at systematically gauging species representativeness in studies of archaeological plant remains. Results indicate that, in addition to discipline‐specific methodological sources of bias, modern agricultural biases may replicate themselves in crop history research and influence understandings of ‘forgotten crops’. Recognizing these biases is an initial stride towards rectifying them and promoting agrobiodiversity in both research and practical applications. Summary So‐called ‘forgotten’ or ‘orphan’ crops are an important component of strategies aimed at preserving and promoting biodiversity. Knowledge of historical cultivation, usage, and geographic and evolutionary trajectories of plants, that is, crop history research, is important for the long‐term success of such efforts. However, research biases in the crops chosen for study may present hurdles. This review attempts to systematically identify patterns in crop species representativeness within archaeology‐based crop history research. A meta‐analysis and synthesis of archaeobotanical evidence (and lack thereof) is presented for 268 species known to have been cultivated for food prior to 1492 CE from the Mediterranean region to South Asia. We identified 39 genera with known crop plants in this geographical and historical context that are currently absent from its archaeobotanical record, constituting ‘orphan’ crops of archaeobotany. In addition, a worldwide synthesis of crop species studied using geometric morphometric, archaeogenetic and stable isotope analyses of archaeological plant remains is presented, and biases in the species represented in these disciplines are discussed. Both disciplinary methodological biases and economic agenda‐based biases affecting species representativeness in crop history research are apparent. This study also highlights the limited geographic diffusion of most crops and the potential for deeper historical perspectives on how crops become marginalized and ‘forgotten’.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.533
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.090
GPT teacher head0.359
Teacher spread0.269 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations24
Published2024
Admission routes1
Has abstractyes

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