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Record W1988898514 · doi:10.3098/ah.2010.84.1.46

Creating an Agricultural World Order: Regional Plant Protection Problems and International Phytopathology, 1878-1939

2010· article· en· W1988898514 on OpenAlexaff
Stéphane Castonguay

Bibliographic record

VenueAgricultural History · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsGeopoliticsAgriculturePolitical scienceConventionInternational tradeRatificationPhytosanitary certificationLawEconomic growthBusinessGeographyEconomicsPoliticsArchaeology

Abstract

fetched live from OpenAlex

Beginning in 1878 with the International Phylloxera Convention of Berne, international conventions have sought to relieve national agricultural industries from two specific burdens. First, by defining phytosanitary practices to be enforced by national plant protection services, these conventions attempted to prevent the introduction of plant diseases and pests into national territories from which they were previously absent. Second, by standardizing these practices - especially through the design of a unique certificate of inspection - the conventions attempted to eliminate barriers such as quarantines affection international agricultural trade. The succession of phytopathological conventions seemed to epitomize the coalescence of an international community against agricultural pests. What actually coalesced was bio-geopolitics wherein plant pathologists and economic entomologists from North America and the British Empire questioned the so-called internationality of the environmental and economic specificities of continental European agriculture, embodied in "international" conventions. Although an international phenomenon, the dissemination of agricultural pests provided opportunities for cooperation on a strictly regional albeit transnational basis that pitted bio-geopolitical spaces against each other. This article retraces the formation of these spaces by analyzing the deliberations of committees and congresses that gathered to define an international agricultural order based on the means to prevent the spread of plant diseases and pests.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.020
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.190
Teacher spread0.175 · 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.

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

Citations13
Published2010
Admission routes1
Has abstractyes

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